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Amazon Nova AI Challenge: Trusted Software Agents, Rules

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The Amazon Nova AI Challenge: Trusted Software Agents (the “Competition”) is a university competition sponsored by Amazon.com Services LLC (“Sponsor”), in which 10 teams of college or university students compete to accelerate advances in artificial intelligence (“AI”). In this year’s Competition track student teams will focus on secure multi-turn development of web applications using coding assistants. Each team will take on the role of either a ‘model developer’ or ‘red team’. The model developer teams will focus on building LLM-driven coding assistants that can complete complex software engineering tasks to modify and extend full stack web applications. In addition to adding capabilities, coding assistants built by model developer teams must prevent accidental or purposeful introduction of security vulnerabilities into the application. To this end, model developer teams will also build bots that simulate malicious users. They will use these malicious user bots to test their systems and then use these same bots to test the resilience of opposing model developer teams during the Competition. 

Red teams, in contrast, will develop LLM-enabled bots capable of identifying and exploiting vulnerabilities found in the web applications generated by the model developer teams. In addition, red teams will build bots that simulate benign users that communicate with the coding assistants to complete software engineering tasks. 

See below for the Competition details.

By applying to or participating in the Competition, you agree to these Official Rules. Please read them carefully and completely.

COMPETITION CALENDAR

Applications to participate in the Competition can be submitted starting November 10, 2025,  through 11.59 PM PST December 7, 2025. The Competition will run from February  2026 through September 2026 (the "Competition Period"). The Competition phases are noted in the calendar below. The dates are approximate and are subject to change at the Sponsor’s sole discretion.

Phases

Starts on

Phase 1: Participant Application Period

11/10/2025

Phase 2: Sponsor Application Review Period

12/8/2025

Phase 3: Participant Notification Period and Onboarding

12/22/2025

Bootcamp

2/1/2026

Phase 4: Initial Build Period

2/4/2026

Phase 5: Tournament Period

March 2026

Phase 6: Finals Event

September 2026

Winners Announced

October 2026

COMPETITION OVERVIEW

Participating University or college teams will focus on advancing the capabilities of coding assistants, while improving their robustness with respect to security principles. Participating teams will aim to make coding assistants for full stack web development that are maximally capable and preclude vulnerabilities and cyber security threats. During the Competition, each team will focus either on building coding assistants (i.e. model developer teams) or developing automated red teaming techniques to identify potential exploits (i.e. red teams). In addition to building their coding assistant, each model developer team will also be responsible for developing a simulated malicious user that they can use for testing their coding assistant and then in tournaments use them to test the resilience of coding assistants built by other teams. In addition to building their red teaming system, each red team will also be responsible for developing a simulated benign user that will interactively prompt each competing coding assistant to complete a specified task. In applying to the competition, each team may choose to apply for either the red team role or the model developer role, or they may choose to apply for both roles and be assigned a role at the Sponsor’s discretion. Throughout the competition, red teams and model developer teams will participate in a series of tournaments. The tournaments will have two phases, in the first ‘build’ phase each of the model developer teams will be matched up with simulated benign and malicious users in multi-turn conversation directed toward completion of several specified tasks on one of more software repos. This phase will be evaluated through automatic testing of the functionality required to be added to the application in each task. In the second, ‘validation’ phase, each of the generated repos will be tested by the automated red teaming agents, which will seek out and exercise vulnerabilities in the applications. 

ELIGIBILITY

To be eligible to participate in the Competition, you must: (1) be enrolled as a full-time undergraduate or post-graduate student at an accredited college or university (other than colleges or universities located in any of the Restricted Jurisdictions defined below) (“Universities”) and remain a full-time student in good standing at such college or university while participating in the Competition; (2) be at or above the age of majority in your country, state, province or jurisdiction of residence at the time of entry into the Competition; and (3) not be a person or entity subject to U.S. export controls or sanctions, including citizens of any of the Restricted Jurisdictions . Competition is void in Cuba, Iran, Syria, North Korea, Sudan, the region of Crimea, the so-called Donetsk People’s Republic (DNR) or Luhansk People’s Republic (LNR), and where prohibited by law (each, a “Restricted Jurisdiction”). People who, during the Competition Period, are directors, officers, employees, interns, and contractors (“Personnel”) of Sponsor, its parents, subsidiaries, affiliates, and their respective advertising, promotion and public relations agencies, representatives, and agents (collectively, “Competition Entities”), immediate families members of such Personnel (parents, siblings, children, spouses, and life partners of each) and members of the households of such Personnel (whether related or not) are ineligible to participate in this Competition. Sponsor reserves the right to verify eligibility and to adjudicate any dispute at any time.
Entrants (“Entrants”) must enter as part of an “Entrant Team” consisting of one or more students from a single college or university. An Entrant is only permitted to be part of one Entrant Team. Any Entrant that is part of more than one Entrant Team may be disqualified, and the corresponding Entrant Teams may be disqualified at the sole discretion of Sponsor. Only one member of the Entrant Team may submit an application on behalf of an Entrant Team, but all those listed on the application are Entrants. All prize money payable to Entrant Teams will be split evenly among eligible Entrants of a winning Entrant Team (based on the pre-tax amount of prize money), as identified in the application, as updated as permitted by these Official Rules, and who maintain full-time student status in good standing at their college or university during the entire Competition Period.
Each team must select a faculty advisor, who, with respect to that team, will act as the official representative for the Entrant Team’s university or college (the “Faculty Advisor”). Each Entrant Team must have its own Faculty Advisor; Faculty Advisors may not represent multiple teams. Faculty Advisors are not members of the Entrant Team and will not receive any portion of any prize. Faculty Advisors must remain full-time employees of the Entrant Team university or college during the entire Competition Period. During the Competition Period, but no later than July 15, 2026, the Faculty Advisor may request to remove members from the Entrant Team or to add additional members to the Entrant Team. The Faculty Advisor must provide an explanation of the reason for the removal or addition, and any proposed new member must provide documentation requested by Sponsor and agree to comply with these Official Rules. Changes to the Entrant Team are subject to Sponsor’s approval in its sole discretion. If at any point during the Competition Period, the Entrant Team’s Faculty Advisor cannot continue to serve as a Faculty Advisor, the Entrant Team may submit a request to Sponsor to select a new Faculty Advisor. Changes to the Entrant Team’s Faculty Advisor are subject to Sponsor’s approval in its sole discretion. If an Entrant Team fails to have a Faculty Advisor at any point in time during the Competition, for any reason, the Entrant Team may be disqualified.
Each Entrant must be eligible to participate in this Competition and comply with these Official Rules or the Entrant, and the Entrant Team associated with that Entrant, may be disqualified. This Competition is subject to all applicable federal, state, territorial, provincial, and local laws. Competition is void where prohibited. By participating in the Competition, all Entrants accept and agree to comply with and abide by these Official Rules and the decisions of the Sponsor which will be final and binding, including the Sponsor’s right to verify eligibility, to interpret these Official Rules, and to resolve any disputes relating to this Competition at any time. Only Entrants may work on the Competition or their entries (e.g., developer systems, coding assistants, red-teaming systems, or user simulators), although employees of the Sponsor may provide support to the Entrant Team during the Competition Period, and the Faculty Advisor, and other students and faculty members at an Entrant Team’s university or college may provide support and advice to the Entrant Team and may co-author the Technical Article (as defined below) or other research papers.

ADDITIONAL REQUIREMENTS

During all phases of the Competition, Sponsor may in its sole discretion require Entrant Teams to provide periodic status updates, reports, or demonstrations of the developer systems, coding assistants, red-teaming system or user simulators. Sponsor may also require Entrant Teams to comply with additional rules, requirements, or procedures that Sponsor determines, in its sole discretion, are necessary for the administration of the Competition. Sponsor may in its sole discretion penalize teams for noncompliance with any rules, requirements, or procedures, including disqualification from the Competition.

Sponsor may provide Entrants selected to participate in the Competition access to generative AI models, software, software platform, software development kits, libraries, APIs, documentation, sample code, data sets, and related materials (“Program Materials ” and “Restricted Program Materials”) that may be used in connection with the Competition. If an Entrant uses any Program Materials or Restricted Program Materials, the Entrant is subject to and agrees to comply with Sponsor’s Program Materials License Agreement or a substantially similar alternative license that may be applied at Sponsor’s sole discretion. Program Materials and Restricted Program Materials may include APIs, data sets, models, model outputs, and other materials that are not public (“Non-Public Materials”).
Each Entrant and Faculty Advisor agrees that they will not disclose, distribute, or otherwise make available any Non-Public Materials to anyone other than other Entrants of their Entrant Team and the Entrant Team’s Faculty Advisor. Each Entrant (and each Faculty Advisor) agrees that they will use Non-Public Materials only in connection with the development of a developer systems, coding assistant, red-teaming system, or user simulator as part of the Competition and in compliance with these Official Rules. Entrants (and Faculty Advisors) may not use Non-Public Materials for any other purpose. Entrants (and Faculty Advisors) must return or destroy all Non-Public Materials (in any form and including, without limitation, all summaries, copies and excerpts of the same) promptly following any request from Sponsor, or if the Entrant Team discontinues the development or operation of its model or red-teaming system. If any Entrant or Faculty Advisor is disqualified from the Competition, leaves the university, or college or otherwise terminates their participation in the Competition, that individual must immediately return or destroy all Non-Public Materials in their possession. Sponsor reserves the right in its sole discretion to impose additional terms and conditions on the use of Program Materials, and to condition access to Program Materials on Entrants’ agreement to those terms and conditions.

Each Entrant Team and Faculty Advisor agrees that they will not copy, disclose, distribute, or otherwise use any output created by a generative AI model during this competition for any purpose other than the development or improvement of their systems as part of this Competition. Entrant Teams may not publish any model output or publish or deploy their systems for any purpose, including in connection with any paper submission, without prior review and approval by Sponsor.

DESCRIPTION OF COMPETITION PHASES

PHASE 1 “Participant Application Period”: Between November  10, 2025 and December 7, 2025, the student leader of each Entrant Team that wishes to enter the Competition may visit  amazon.science/nova-ai-challenge (the “Competition Site”) to submit their entry information via the YouNoodle, Inc. (“YouNoodle”) application portal, including but not limited to: complete names, contact information, and resumes of all Entrant Team members, proof of university or college enrolled status (e.g., verification of enrollment or an uploaded copy of Entrants’ student IDs), name and contact information of up to three sponsoring Faculty Advisor(s) from the Entrant Team’s university or college , and a bio for each Entrant Team member and Faculty advisor(s).

Sponsor will consider applications by multiple different teams from a single institution, but each Entrant Team must have their own Faculty Advisor, and there can be no overlap in the composition of the Entrant Teams or Faculty Advisors. If more than one Entrant Team is accepted from any university or college, the Entrant Teams will be expected to work independently, and any collaboration or coordination among Entrant Teams will be grounds for disqualification.

Entry Applications may be submitted at any time during the Participant Application Period. Only one individual per Entrant Team, preferably the team lead, may submit an Entry Application on behalf of their Entrant Team. Other members of the Entrant Team must accept the invitation to join the team via the YouNoodle application portal. All Entrants must create an account with YouNoodle if they have not done so already to submit an Entry Application or accept an invitation to join an Entrant Team and participate in the Competition. Creating and maintaining a YouNoodle account is free of charge. All Entry Applications must be complete when the Participant Application Period closes at 11:59 pm Pacific Time on the last day of the Participant Application Period. Entry Applications are not complete until all the online prompts and instructions to upload the Entry Application have been properly followed, the Official Rules have been accepted, and all Entrant Team members and the Faculty Advisors have accepted their invitations to join the Entrant Team via the YouNoodle application portal. Entry Applications may not be revised once submitted. Once submitted, Entry Applications will not be returned and become the property of the Sponsor.

Entry terms: Determination of eligibility and compliance with these Official Rules and any other requirements imposed by Sponsor will be in the sole discretion of the Sponsor. By entering, Entrants represent that all information and materials submitted to Sponsor in connection with the Competition:

  1. are the original work of the Entrant Team or an update to an original work of the Entrant Team;
  2. do not infringe or violate the rights of any third party, including but not limited to copyrights, trademarks or copyrighted material not owned by the Entrant Team, contract and licensing rights, rights of publicity or privacy, moral rights, or any other intellectual property rights; and
  3. are not subject to any third-party agreements, and that Sponsor will not be required to pay or incur any sums to any person or entity as a result of its exercise of any rights granted under these Official Rules.

As referenced above, each Entrant Team will be required to apply for at least one role (i.e., either the red-team role or model developer role). Alternatively, Entrant Teams can choose to apply for both roles and Sponsor will assign one of the two roles to a team based on the Entry Application in Sponsor’s sole discretion.

PHASE 2 “Sponsor Application Review Period”: All eligible Entry Applications will be reviewed by the Sponsor. Sponsor will select up to ten (10) Entrant Teams for the Competition in its sole discretion, based on the following criteria:

  • The technical merit of the approach;
  • The novelty of the idea; and
  • An assessment of the Entrant Team’s ability to execute their plan.

PHASE 3 “Participant Notification Period”: Entrant Teams selected by Sponsor to participate in the Competition will be notified by email at the email address provided in the application portal. Entrant Teams acknowledge that some Entrant Teams may include Entrants and Faculty Advisors who participated in prior competitions and other promotions offered by Sponsor.

Stipends: Each Entrant Team selected to participate in the Initial Build Period will be eligible to receive a restricted research grant of $250,000 U.S. dollars (paid in any number of installments as determined by Sponsor in its sole discretion, subject to Entrant Team’s continued participation in and eligibility for the Competition). These restricted research grants will be awarded to the universities and not the Entrant Teams or any individual Entrant, and will be subject to the university or college signing and returning any agreements or other documents required by Sponsor (including IRS forms W-9 and/or W-8), and to the university or college agreeing in writing that no more than 35% of the research grants may be allocated to administrative fees. Entrant Teams will not be eligible to begin participating in the Competition until all required agreements and other documentation have been completed by the respective university or college. The grants are intended to support two full-time students or the equivalent of two full-time students during the Competition and one month of the Faculty Advisor’s salary. Each university or college will be responsible for allocating and managing the funds within these guidelines and for payment and reporting of any required taxes, withholdings, fees, or duties. Sponsor is not responsible for managing the funds, including their allocation or distribution by the university or college, after they are paid to the university or college. Each member of an Entrant Team whose university or college receives a stipend award, and its Faculty Advisor, will also receive free AWS services to support the development of their model or red-teaming system (subject to reasonable limitations set by Sponsor), and support from the Sponsor as determined by Sponsor.

Stipends are non-transferable except as directed by Sponsor. No stipend substitutions or cash redemptions are allowed except as designated by Sponsor. Except where prohibited by law, all federal, state, provincial, or other tax liabilities or withholdings are the responsibility of the university or college and the Sponsor will not be responsible for any tax deductions which may be necessary, except that Sponsor may withhold taxes as required by law. Universities are responsible for any costs and expenses associated with stipend acceptance and use. If an Entrant Team withdraws from the Competition or does not remain compliant with these Official Rules, Sponsor will be relieved of any obligation to pay any remaining portion of the stipend to the Entrant Team’s university or college All details relating to the stipend not specified herein shall be determined solely by Sponsor.

Boot Camp: Selected Entrant Teams will be invited to a Competition Boot Camp (“Boot Camp”), which Sponsor intends to hold in February 2026 at Sponsor’s headquarters in Seattle, Washington or alternative location as determined by Sponsor. Entrant Teams will be expected to use the stipend towards any uncovered costs associated with the Boot Camp. Faculty Advisors and at least 1 student team member are expected to attend the Boot Camp. In the event that Sponsor is unable to hold a Boot Camp, Sponsor may reschedule or cancel the Boot Camp at its sole discretion, and Sponsor is not required to reimburse any expenses incurred by Entrant Teams.

PHASE 4 “Initial Build Period”: Selected Entrant Teams will develop their model or red-teaming system. Sponsor will provide each Entrant Team with certain Program Materials or Restricted Program Materials by the beginning of the Initial Build Period.

PHASE 5 “Tournament Period”: The Tournament Period will include a series of tournaments. The number of individual tournament rounds, and the exact start and end dates of each of the tournaments will be announced prior to the start of the first tournament. On the start date of each of the tournaments, red teams will submit their red-teaming systems and benign user simulator to the sponsor. On the start date of each of the tournaments. model developer teams will submit their coding assistant and malicious user simulator to the Sponsor. The Sponsor will then execute the build phase of the tournament, matching the different benign user simulators and malicious user simulators with each of the relevant coding assistants. Utility performance will be determined through automated tests associated with each development task. Following the build phase, in the validation phase, the Sponsor will match up each red teaming system with each relevant created applications and use a combination of automated testing and human evaluation to score the identified vulnerabilities and exploits in the applications. Red teams and model developer teams will be ranked separately. Overall ranking of model developer teams will be based on a combination of utility performance on the specified task and defense success in being resilient to exploits attempted by the red teaming bots. Overall ranking of red teams will be based on a combination of utility performance on the specified tasks and attack success in identification and execution of exploits by the red teaming bots.
 Evaluation results may be provided to the Entrant Teams, as determined by Sponsor in its sole discretion. Both red teams and model developer teams may improve their systems in between tournament rounds, after the Sponsor notifies them that a tournament round is complete. Teams may not modify their model or red-teaming systems while the tournament round is ongoing. To move to the Finals Event, teams must meet minimum success criteria that will be established and provided to Entrant Teams during the Tournament Period. Teams that do not meet the criteria at the end of the last tournament may be eliminated following the end of the current Tournament Period. 

Summit: Sponsor at its sole discretion may choose to hold a summit at the end of the Competition where participants discuss their findings and announce the winners of the Competition. Sponsor may elect to provide each finalist Entrant Team reimbursement for the cost of airline tickets (non-refundable coach class booked through Sponsor at least 14 days in advance) to the site of the Summit where Entrant teams will present their innovations from the competition, and the provision of hotel rooms at the site of the Summit or such other event, to permit members of each Entrant Team (up to a maximum number of members determined by Sponsor) and the Faculty Advisor to attend the Summit or such other event. Travel expense subsidies and access to the event may be subject to tax information reporting and withholding to the extent required by law.

Disclosure of Third-Party Funding. If any Entrant Team receives any third-party funding to facilitate its participation in this Competition, such funding must be disclosed to Sponsor no later than the last date of the Tournament Period, along with any requirements imposed on the Entrant Team in connection with the funding. Entrant Teams may not accept or use any third-party funding if acceptance or use of that funding, or any requirements imposed in connection with that funding, conflicts with these Official Rules.

Technical Publication: No later than the first day of the final tournament round in the Tournament period or any other date determined by the Sponsor, all participating Entrant Teams must submit to Sponsor a technical article including (a) the technical approach for their developer systems, coding assistant, red-teaming system, and user simulator, and (b) any comparative experiments performed by the Entrant Team and results of those experiments (a “Technical Article”). Entrant Team’s Technical Article must include sufficient detail to permit other researchers to replicate the work. However, Technical Articles may not include any Non-Public Materials or other confidential information of Sponsor or its affiliates. If a Technical Article does not provide sufficient detail to replicate the work, Sponsor may require the Entrant Team to provide Sponsor any additional information needed to replicate the work. Sponsor will publish the Technical Articles in connection with the Finals Event. Prior to the publication, Sponsor will not disclose Technical Articles to third parties. Entrant Teams may update their Technical Articles prior to the Finals Event.

In addition to the required Technical Articles, Entrants may publish other technical articles describing their work (“Additional Articles”). However, prior to submitting any technical articles to any publication, conference, or other venue for publication, Entrant Teams must obtain Sponsor’s written approval. Additional Articles may not include any Non-Public Materials or other confidential information of Sponsor or its affiliates. Entrants must submit any Additional Articles to Sponsor for review and comment at least two weeks prior to the submission deadline and must make, prior to submission, any changes or deletions requested by Sponsor to protect confidential or other sensitive information.

PHASE 6 “Finals Event”: Sponsor will hold a multi-day Finals Event that will be structured as follows. Sponsor will recruit a panel of coding and cybersecurity experts to serve as judges. These human judges will come onsite to the Sponsor’s campus (Entrant teams will not be onsite during the Finals Event) for the Finals Event. Expert human judges will evaluate both red teams and model developer teams’ success in finals. 

Human judges will work with model developer team’s coding assistants as both malicious and benign users and evaluate their effectiveness and ease of use. Human judges will also observe interaction between user simulator and coding assistants and inspect the results of automated security teaming bots. Human judges will conduct manual red teaming of generated applications. The final ranking and determination of winners for model developers will depend on 1) ease of use of coding assistant to complete tasks 2) quality of solution and 3) resistance of the resulting solution to attempted exploits. The final ranking and determination of winners for red teams will depend on 1) effectiveness in automated identification of exploits 2) quality of user simulation. 

Winners Announcement Event: Sponsor may elect to provide each finalist Entrant Team reimbursement for the cost of airline tickets (non-refundable coach class booked through Sponsor at least 14 days in advance) to the site of the event announcing the winners of the Competition, and the provision of hotel rooms at the site of the Event or such other event, to permit members of each finalist Entrant Team (up to a maximum number of members determined by Sponsor) and the Faculty Advisor to attend the Event or such other event. Travel expense subsidies and access to the event may be subject to tax information reporting and withholding to the extent required by law.

PHOTO, UNIVERSITY LOGO AND TEAM WRITE-UP REQUIREMENTS
Each selected Entrant Team must provide a team photo including all the team members and faculty advisor within 15 days of selection. No photo collage of individual pictures will be accepted. The team photos must be rectangular or square. Entrant Team photos that are strongly horizontal or vertical will not be accepted. The Entrant Team must provide a 50-word write-up about each individual team member and faculty advisor(s) within 15 days of selection. The write-up must be written in the third person. Every subsequent reference to the member must be a pronoun or last name. e.g.,: “Tom Smith is a computer science PhD student at ABC university, he/Smith is studying..” When requested by Sponsor, Entrant Teams must provide a high-quality university logo that the Sponsor is free to use for any marketing or promotional content for the Amazon Nova AI Challenge program.

PRIZES

Overall Performance Prize
Following the Finals Event, the two finalist red-teaming systems that attain the two highest ranks among the finalist red-teaming systems and the two finalist coding assistants that attains the two highest ranks among the finalist coding assistants will be the First-Place and Second-Place winners of the Overall Performance prizes. If there is a tie in the scores for any prize, Sponsor will rank the systems based on their Tournament Period performance. Sponsor’s decisions are final and binding in all matters relating to this Competition, including the determination of prize winners.

First-Place Overall Performance Model (1 winner): The Entrant Team that receives the highest rank for a coding assistant will receive $250,000 U.S. dollars awarded in the form of checks divided equally among all members of that Entrant Team.
Second-Place Overall Performance Model (1 winner): The Entrant Team that receives the second highest rank for a coding assistant will receive $100,000 U.S. dollars awarded in the form of checks divided equally among all members of that Entrant Team.
First-Place Overall Performance Red-Teaming System (1 winner): The Entrant Team that receives the highest rank for a red-teaming system will receive $250,000 U.S. dollars awarded in the form of checks divided equally among all members of that Entrant Team.
Second-Place Overall Performance Red-Teaming System (1 winner): The Entrant Team that receives the second highest rank for a red-teaming system will receive $100,000 U.S. dollars awarded in the form of checks divided equally among all members of that Entrant Team.

Prize Conditions: Prizes are non-transferable except as directed by Sponsor. No prize substitutions are allowed. Except where prohibited by law, all federal, state, provincial, or other tax liabilities are the responsibility of the prize winners, Sponsor will not be responsible for any tax deductions which may be necessary, and Sponsor reserves the right to withhold taxes as required by law. Prize winners will be responsible for paying all costs and expenses related to the prize that are not specifically mentioned, including, but not limited to, taxes, withholdings, and any other expenses that might reasonably be incurred by the winner in receiving or using the prize. All prizes awarded will be subject to any taxes Sponsor is required by law to withhold as well as applicable sales, use, gross receipts, goods and service, or similar transaction-based taxes. IF TAXES ARE APPLICABLE TO THE PRIZE(S), IT IS THE RESPONSIBILITY OF THE WINNER TO PAY TO THE APPROPRIATE AUTHORITIES. PAYMENTS TO COMPETITION WINNERS ARE SUBJECT TO THE EXPRESS REQUIREMENT THAT THE WINNER SUBMIT TO SPONSOR ALL DOCUMENTATION REQUESTED BY SPONSOR (INCLUDING FORMS W-9 OR W-8BEN AS REQUESTED BY SPONSOR) TO PERMIT COMPLIANCE WITH ALL APPLICABLE STATE, FEDERAL, LOCAL AND FOREIGN (INCLUDING PROVINCIAL) TAX REPORTING AND WITHHOLDING REQUIREMENTS. Prize winners are responsible for ensuring that the tax documentation submitted to Sponsor complies with all applicable tax laws and requirements. If a winner fails to provide the documentation or submits incomplete documentation, the prize may be forfeited and Sponsor may, in its sole discretion, select an alternate winner. Sponsor will divide all awards that are payable to any Entrant Team evenly among the Entrant Team members and distribute accordingly. Designation as a prize winner is subject to Entrant’s proof of compliance with these Official Rules, maintaining compliance with these Official Rules and approval by Sponsor. All details of prizes not specified herein shall be determined solely by Sponsor.

PRIVACY: Entrants and Faculty Advisors acknowledge and agree that Sponsor may collect, store, share, and otherwise use personally identifiable information provided during the application process and the Competition, including, but not limited to, name, mailing address, phone number, and email address. All personally identifiable information collected is subject to and will be used in accordance with Sponsor’s Privacy Notice ( www.amazon.com/privacy) and YouNoodle’s Privacy Policy ( www.younoodle.com/privacy), including for administering the Competition and verifying Entrants’ and Faculty Advisors’ identities, addresses, and telephone numbers in the event an entry qualifies for a prize. YouNoodle’s servers are located in the United States. By participating in this Competition, Entrants and Faculty Advisors authorize the transfer of personal data to the United States for purposes of administering the Competition, conducting publicity about the Competition, and additional purposes consistent with Sponsor’s goals or the Competition goals. By entering the Competition, Entrants and Faculty Advisors consent to Sponsor’s and YouNoodle’s collection, and Sponsor’s use and disclosure of entrants’ personally identifiable information for these purposes. The data controller for information collected by Sponsor is Amazon.com Services LLC, 410 Terry Ave North, Seattle, Washington 98109, USA.

INTELLECTUAL PROPERTY: By entering the Competition, each Entrant and Entrant Team represents and warrants that he or she has obtained all of the rights, licenses, and permissions in writing that are otherwise necessary for the Entrant Team to operate or distribute the model or red-teaming system and to grant to Sponsor the licenses set forth in these Official Rules and in the Developer Agreement. Entrants MAY NOT submit models or red-teaming systems created by any person other than themselves or their Entrant Team members.
As between Sponsor and Entrant Teams, models or red-teaming systems created by Entrant Teams will remain the property of the respective Entrant Teams or their university or college, excluding any Program Materials or Restricted Program Materials incorporated in the systems, which will remain the property of Sponsor. All output generated by any model or red-teaming system during the course of the Competition will be the property of Sponsor, and Entrant Teams will have limited rights to use the output for the sole purpose of improving or training their modes or systems for the purpose of this Competition. By submitting a model or red-teaming system in this Competition, each Entrant and Entrant Team represents and warrants that they own, or otherwise have the right to use and license, all of the intellectual property and other rights in and to the model or red-teaming system. Each Entrant and Entrant Team hereby grants Sponsor and its affiliates a non-exclusive, perpetual, irrevocable, worldwide, and royalty-free license to make, have made, use, sell, offer for sale, import, export, license, exploit, promote, reproduce, make available, publicly display, publicly perform, create derivative works of, and otherwise exercise all intellectual property and other rights in and to any concepts, works, inventions, information, designs, programs, software, or other materials that the Entrant or Entrant Team develops or submits in connection with the Competition or the creation of the model or red-teaming system, including any of the foregoing included or described in any Technical Article or other materials provided to Sponsor. In addition, upon Sponsor’s request, all Entrants and Entrant Teams must provide Sponsor all source code, datasets and algorithms developed in connection with the Competition. Each Entrant agrees to do or perform, or cause to be done and performed, all such further acts and things, and execute and deliver all such other agreements, certificates, instruments, and documents as Sponsor may reasonably request in order to carry out the intent and accomplish the purposes of the foregoing license.
Except where prohibited, each Entrant and Entrant Team further consents (and agrees to sign any additional documents required by Sponsor to formalize, effect, or perfect such consent) to Competition Entities’ model or red-teaming systems pursuant to these Official Rules and the use of any Entrant or Entrant Team names, likeness, biographical information, and voice in advertising, publicity, trade, and other marketing and promotional materials (including video, audio, and print through all means of distribution) worldwide without compensation, notice, or approval, and disclaims any ownership rights to the content of such materials.

Waiver, Release, and Limitation of Liability
EACH ENTRANT ACCEPTS THE CONDITIONS STATED IN THESE OFFICIAL RULES, AGREES TO BE BOUND BY THE DECISIONS OF SPONSOR, WARRANTS THAT THE ENTRANT IS ELIGIBLE TO PARTICIPATE IN THIS COMPETITION, AND AGREES TO RELEASE, INDEMNIFY, AND HOLD HARMLESS THE COMPETITION ENTITIES AND THE PERSONNEL OF EACH FROM AND AGAINST ANY AND ALL CLAIMS, LOSSES, LIABILITY, AND DAMAGES OF ANY KIND (INCLUDING REASONABLE ATTORNEYS’ FEES AND EXPENSES) ASSERTED AGAINST ANY OF THEM, INCURRED OR SUSTAINED IN CONNECTION WITH OR ARISING OUT OF ENTRANT’S PARTICIPATION IN THIS COMPETITION OR ANY TRAVEL OR OTHER ACTIVITY RELATED THERETO, USE OF ANY MODEL OR RED-TEAMING SYSTEM OR RIGHTS THEREIN, OR BREACH OF ANY AGREEMENT OR WARRANTY ASSOCIATED WITH THE COMPETITION, INCLUDING THESE OFFICIAL RULES. ANY ATTEMPT TO DELIBERATELY DAMAGE ANY WEBSITE OR UNDERMINE THE LEGITIMATE OPERATION OF THE COMPETITION MAY BE A VIOLATION OF CRIMINAL AND CIVIL LAWS AND, SHOULD SUCH AN ATTEMPT BE MADE, THE COMPETITION ENTITIES AND EACH OF THEIR LICENSEES RESERVE THE RIGHT TO SEEK ANY AND ALL REMEDIES AVAILABLE FROM ANY PERSONS RESPONSIBLE FOR ANY SUCH ATTEMPT TO THE FULLEST EXTENT PERMITTED BY LAW.

Each Entrant hereby acknowledges and agrees that the relationship between themselves and the Competition Entities is not a confidential, fiduciary, or other special relationship, and that the Entrant’s decision to provide the entry to Sponsor for purposes of the Competition does not place the Competition Entities in a position that is any different from the position held by members of the general public with regard to elements of the entry, other than as set forth in these Official Rules. Each Entrant understands and acknowledges that the Competition Entities have wide access to the models, technology, designs, and other materials, and that new ideas are constantly being submitted to them or being developed by their own employees. Each Entrant also acknowledges that many ideas may be competitive with, similar to, or identical to the model or red-teaming system submission in theme, idea, format, or other respects. Each Entrant acknowledges and agrees that such Entrant will not be entitled to any compensation as a result of Competition Entities' use of any such similar or identical material that has or may come to Competition Entities, or any of them, from other sources. Entrants acknowledge that other Entrants and Entrant Teams may have created ideas and concepts contained in their model or red-teaming system's design that may have familiarities or similarities to their system's design, and that they will not be entitled to any compensation or right to negotiate with the Competition Entities because of these familiarities or similarities.

Entrants further agree that the Competition Entities are not responsible for the following: (a) electronic transmissions, model or red-teaming system, entries, or notifications that are lost, late, stolen, incomplete, damaged, garbled, destroyed, misdirected, or not received by Sponsor or their agents for any reason; (b) any problems or technical malfunctions, errors, omissions, interruptions, deletions, defects, delays in operation or transmission, communication failures, and/or human error that may occur in the transmission, shipping errors or delays, receipt or processing of entries or related materials; or for destruction of or unauthorized access to, or alteration of, entries or related material; (c) failed or unavailable hardware, network, software, or telephone transmissions, damage to Entrants’ or any person’s computer and/or its contents related to or resulting from participation in this Competition; (d) causes that jeopardize the administration, security, fairness, integrity, or proper conduct of this Competition; (e) any entries submitted in a manner that is not expressly allowed under these Official Rules (all such entries will be disqualified); or (f) any printing errors in these Official Rules or in any advertisements or correspondence in connection with this Competition or the tabulation of Interaction Ratings or scores. Sponsor reserves the right, in its sole discretion, to cancel or suspend this Competition should virus, bugs, fraud, hacking, or other causes corrupt the administration, security, or proper play of the Competition, or in the event Sponsor does not receive a minimum of two qualified entries from separate eligible Entrant Teams. Sponsor further reserves the right, in its sole discretion, to cancel or suspend this Competition or to reschedule or reformat events, including without limitation the Summit or Finals Event, should Sponsor be prevented, in any manner whatsoever, from holding this Competition or any event due to any present or future law (whether or not valid); any act of God, earthquake, fire, flood, epidemic (including, without limitation, any pandemic), accident, explosion or casualty; any civil disturbance or armed conflict; or any other cause of any similar nature outside of Sponsor’s control. In all such cases, notice to this effect will be posted on the Competition Site and prizes to the extent awarded will be awarded as determined by Sponsor prior to cancellation. If, in Sponsor’s opinion, there is any suspected or actual evidence of electronic or non-electronic tampering with any portion of the Competition or if technical difficulties compromise the integrity of the Competition, the Sponsor reserves the right to void suspect entries and/or terminate the Competition and determine whether to award prizes in its sole discretion. Sponsor reserves the right, in its sole discretion, to disqualify any individual found by Sponsor to have tampered with the entry process or entry materials, otherwise interfered with the proper administration of the Competition, or violated these Official Rules.

DISPUTES: Except where prohibited, you agree that: (1) any and all disputes, claims, and causes of action arising out of or connected with this Competition or any prize awarded shall be resolved individually, without resort to any form of class action; (2) any and all claims, judgments, and awards shall be limited to actual out-of-pocket costs incurred, including costs associated with entering this Competition, but in no event attorneys’ fees; (3) the Competition Entities shall not be liable for, under no circumstances will you be permitted to obtain awards for, and you hereby waive all rights to claim, indirect, punitive, incidental, and consequential damages and any other damages (other than for actual out-of-pocket expenses), and any and all rights to have damages multiplied or otherwise increased. All issues and questions concerning the construction, validity, interpretation, and enforceability of these Official Rules, or the rights and obligations of the Entrant and Sponsor in connection with the Competition, shall be governed by, and construed in accordance with, the laws of the State of Washington without giving effect to any choice of law or conflict of law rules (whether of the State of Washington or any other jurisdiction), which would cause the application of the laws of any jurisdiction other than the State of Washington. You irrevocably submit to venue and exclusive personal jurisdiction in the federal and state courts in Seattle, King County, Washington, USA, for any dispute arising under these Official Rules or in connection with the Competition, and you waive all objections to jurisdiction and venue of such courts.

SPONSOR: Amazon.com Services LLC, 410 Terry Ave North, Seattle, Washington 98109, USA.

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Applied Scientist - LLM, Alexa
GB, Cambridge
Alexa is looking for an Applied Scientist with a strong background in Natural Language Processing (NLP) and Large Language Models (LLMs) to help build state-of-the-art conversational systems. In this role, you will collaborate with a large team of scientists training the Large Language Models that power the Alexa stack, as well as software engineers serving them in production systems. You will own solutions end-to-end: from ideation and research through to production deployment, enabling conversational assistants to support external tools, leverage diverse sources of information, and deliver novel reasoning capabilities to millions of Alexa customers. Key job responsibilities As an Applied Scientist, you will develop innovative solutions to complex problems to extend the functionalities of conversational assistants. You will use your technical expertise to research and implement novel algorithms and modelling solutions in collaboration with other scientists and engineers. You will analyze customer behaviors and define metrics to enable the identification of actionable insights and measure improvements in customer experience. You will communicate results and insights to both technical and non-technical audiences through written reports, presentations and external publications. You would be able to bi-modal on science and engineering: someone who combines strong scientific foundations with the execution skills to ship high-quality solutions. A day in the life As an Applied Scientist on the Alexa Science team, you'll drive innovation in evaluating new product experiences while discovering novel approaches to enhance model capabilities and enrich customer interactions. You'll collaborate with cross-functional teams of engineers and scientists to identify root causes of model and system integration issues, continuously improving the end-to-end customer experience. You'll partner closely with scientists developing and fine-tuning large language models, engineers building low-latency inference infrastructure, and product teams defining customer experience metrics. About the team We are a team of applied scientists and engineers building the intelligence layer that powers Alexa+. Our work sits at the intersection of large language models, decision-making under uncertainty, and production ML systems. What we build directly shapes the customer experience: determining which models serve their requests, optimizing response latency, and creating natural, seamless interactions. We're a collaborative team that values rigorous experimentation, clear communication, and delivering solutions that perform at scale in real-world environments.
Applied Scientist II, Perception
US, CA, San Francisco
Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Applied Scientist in Robot Perception, you will be at the forefront of this transformation. You will develop and deploy state-of-the-art perception algorithms that enable robots to truly understand and interact with the physical world — bridging the gap between theoretical research and real-world impact. Bringing deep expertise in Computer Vision and a nuanced understanding of the capabilities and limitations of modern Vision-Language Models (VLMs), you will innovate boldly and push the boundaries of what's possible. Our vision for the Perception layer is ambitious: to enable seamless, intelligent interaction between the user, the robot, and its environment. This is a rare opportunity to work at the intersection of deep learning, large language models, and robotics — contributing to research that doesn't just advance the field, but reshapes it. You will collaborate with world-class teams pioneering breakthroughs in dexterous manipulation, locomotion, and human-robot interaction, all at an unprecedented scale. Join us in building intelligent robotic systems that will define the future of automation and human-robot collaboration. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions
Applied Scientist, Machine Learning Accelerator - Annapurna Labs
US, TX, Austin
Our team is involved with pre-silicon design verification for custom IP. A critical requirement of the verification flow is the requirement of legal and realistic stimulus of a custom Machine Learning Accelerator Chip. Content creation is built using formal methods that model legal behavior of the design and then solving the problem to create the specific assembly tests. The entire frame work for creating these custom tests is developed using a SMT solver and custom software code to guide the solution space into templated scenarios. This highly visible and innovative role requires the design of this solving framework and collaborating with design verification engineers, hardware architects and designers to ensure that interesting content can be created for the projects needs. Key job responsibilities Develop an understanding for a custom machine learning instruction set architecture. Model correctness of instruction streams using first order logic. Create custom API's to allow control over scheduling and randomness. Deploy algorithms to ensure concurrent code is safely constructed. Create coverage metrics to ensure solution space coverage. Use novel methods like machine learning to automate content creation. About the team Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for customers who require specialized security solutions for their cloud services. Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
Member of Technical Staff, Multimodal Agents, AGI Autonomy
US, CA, San Francisco
Amazon AGI Lab is a frontier research and product team combining the speed of a startup with Amazon’s scale and resources. We build agents that can perceive, reason, and take action to complete real-world tasks. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We're hiring a principal engineer who can take models from prototype to production and build the systems that make them run reliably at scale. The bar is end-to-end ownership: your work can range from working alongside researchers to build novel architectures, to being the person who decides what the agent runtime looks like, where the data lives, and how we know it's delivering value. Key job responsibilities - Set the technical direction for the team - Partner closely with researchers to take emerging VLM and agent ideas from prototype to robust, instrumented systems that can be evaluated, improved, and scaled - Create tooling that accelerates research and engineering velocity - Raise the engineering bar for the team through technical design reviews, mentoring, principled architecture, high-quality code, observability, and operational excellence - Influence the broader AGI organization by identifying reusable primitives, writing clear technical strategy, and creating systems that other teams can build on - Be a thought leader & represent the lab externally by sharing ideas through thoughtful writing, conference talks, research publications, and open-source contributions, helping advance the field while raising the visibility and impact of the team’s work
Applied Scientist, Amazon Precision Match
US, WA, Seattle
We are seeking an Applied Scientist to join the Amazon Precision Match (APM) team within Customer Journey, Network Solutions. APM is a transformative initiative replacing Amazon's legacy queue-based customer service routing with intelligent algorithmic matching — connecting customers with the best available service option based on their needs and Customer Service Associates (CSA) capabilities. This role will drive the science behind a high-scale system with significant projected impact on operational efficiency and customer experience. You will work at the intersection of recommendation systems, real-time ML inference, and large-scale experimentation to redefine how Amazon serves its customers. Key job responsibilities - Design, develop, and optimize ML-based matching algorithms that pair customers with optimal CSAs based on contact complexity, intent, and CSA skill profiles. - Build and iterate on feature engineering pipelines across CSA-level (skills, tenure, sentiment handling), contact-level (intent, complexity, urgency), and customer-level (language, communication style) attributes. - Run offline simulations on large-scale historical contact data and design statistically rigorous A/B experiments to validate matching improvements. - Develop real-time low-latency scoring and inference systems for production contact routing. - Address the cold start problem for new CSAs and build continuous model retraining infrastructure using production feedback. - Partner with CS Economics, Capacity Planning, and Quality teams on experiment design and results interpretation. - Evolve the matching framework from individual CSA ranking to set-based optimization balancing performance and operational sustainability. A day in the life You will spend your days iterating on matching models, analyzing experiment results from live production traffic, and collaborating with engineers and product managers to translate science insights into system improvements. You'll partner with the Customer Service Economics team to design experiments, review simulation outputs, and present findings to senior leadership. You'll also deep-dive into CSA behavioral patterns, contact transcripts, and performance data to identify new matching signals and continuously improve the algorithm. About the team The Amazon Precision Match team is a high-impact, fast-moving science and engineering team within Customer Journey, Network Solutions. Our mission is to ensure every Amazon customer is connected with the right service option at the right time — improving customer experience while driving operational efficiency at scale. We value intellectual curiosity, rigorous experimentation, and a bias for action. We operate with a continuous improvement flywheel: offline simulation, A/B testing, and production rollout. We collaborate closely with Customer Service Operations, Capacity Planning, Quality, and partner science teams across Amazon.
Applied Scientist, Pricing Science
US, WA, Seattle
Amazon's Pricing Science is seeking a driven Applied Scientist to harness planet scale multi-modal datasets, and navigate a continuously evolving competitor landscape, in order to regularly generate fresh customer-relevant prices on billions of Amazon products worldwide. We are looking for a talented, organized, and customer-focused applied researchers to join our Pricing Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our pricing algorithms across all products listed on Amazon. This role requires an individual with exceptional machine learning and predictive modeling skills, causal and experimental evaluation experience, excellent cross-functional collaboration skills and business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work independently to deliver business impact. Key job responsibilities - See the big picture. Understand and develop science to influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques - Build strong collaborations. Partner with product, engineering, and data teams within Pricing & Promotions to deploy models at Amazon scale - Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, reinforcement learning, causal ML, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems - Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. - Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems. A day in the life We are hiring an applied scientist to drive our pricing optimization initiatives. The Price Optimization science team drives cross-domain and cross-system improvements through: - Invent and deliver price optimization, simulation, and competitiveness tools for Sellers. - Promotion optimization initiatives exploring CX, discount amount, and cross-product optimization opportunities. - Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods) Price is a highly relevant input into many partner-team architectures, and is highly relevant to the customer, therefore this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication. About the team About the team: the Pricing Optimization team within P2 Science owns price quality, discovery and discount optimization initiatives, including criteria for internal price matching, price discovery into search, p13N and SP, pricing bandits, and Promotion type optimization. We leverage planet scale data on billions of Amazon and external competitor products to build advanced optimization models for pricing, elasticity estimation, product substitutability, and optimization. We preserve long term customer trust by ensuring Amazon's prices are always competitive and error free.
Senior Applied Scientist , Sponsored Products
US, NY, New York
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. We are seeking a technical leader for our Supply Science team. This team is within the Sponsored Product team, and works on complex engineering, optimization, econometric, and user-experience problems in order to deliver relevant product ads on Amazon search and detail pages world-wide. The team operates with the dual objective of enhancing the experience of Amazon shoppers and enabling the monetization of our online and mobile page properties. Our work spans ML and Data science across predictive modeling, reinforcement learning (Bandits), adaptive experimentation, causal inference, data engineering. Key job responsibilities Search Supply and Experiences, within Sponsored Products, is seeking a Senior Applied Scientist to join a fast growing team with the mandate of creating new ads experience that elevates the shopping experience for our hundreds of millions customers worldwide. We are looking for a top analytical mind capable of understanding our complex ecosystem of advertisers participating in a pay-per-click model– and leveraging this knowledge to help turn the flywheel of the business. As a Senior Applied Scientist on this team you will: --Act as the technical leader in Machine Learning and drive full life-cycle Machine Learning projects. --Lead technical efforts within this team and across other teams. --Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production. --Run A/B experiments, gather data, and perform statistical analysis. --Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. --Work closely with software engineers to assist in productionizing your ML models. --Research new machine learning approaches. --Recruit Applied Scientists to the team and act as a mentor to other scientists on the team. A day in the life The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced, high-energy and ever-changing environment. The drive and capability to shape the direction is a must. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to customers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon
Data Scientist, Seller Fee Science
IN, KA, Bengaluru
The Seller Fee Science Team integrates economic modeling, machine learning, and artificial intelligence to guide fee strategy, quantify its impact, and ensure fees are accurately computed and explained for billions of transactions between Amazon selling partners and customers. We help build the foundations for growing selling partner businesses, bringing the best selection and prices to Amazon customers, and helping Amazon leaders make and implement high impact decisions that optimally balance profitability and growth. Our team brings together world-class economists, physicists, mathematicians, and computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact. As an data scientist on our team, this role will focus on the application of data analysis, econometrics, machine learning, and artificial intelligence to measure and predict Amazon's P&L, with emphasis on fee revenue. This blends the tools of data science, statistics, and ML/AI. Your work will shape not only how fees are decided, but how they are interpreted and planned. We are seeking scientists who are motivated by first principles, disciplined experimentation, and the technical challenge of deploying ideas at global scale. This is an opportunity to work on consequential problems where analytic rigor meets real-world complexity, and where your analysis, models, algorithms, and systems will directly influence the experience of millions of sellers. If you are driven to build elegant solutions to hard problems—and to see them operate in production at meaningful scale—we would welcome the opportunity to build with you. Key job responsibilities ** Translate ambiguous business challenges into well-defined scientific problems with measurable impact. ** Identify opportunities to improve fee revenue measurement, prediction, planning, structure, and level. ** Identify opportunities to improve measurement, and prediction of other items of the P&L, at appropriate levels of granularity. ** Design, develop, and deploy econometric or AI/ML models that improve our understanding of the relationship between fees and costs, or predict fee revenue, and other elements of the P&L. ** Partner closely with finance and fee strategy teams to formulate scientific questions, communicate results, and productionalize solutions. **Apply rigorous simulation methods to validate models and quantify business impact at scale. **Communicate scientific innovations and results clearly to cross-functional stakeholders and contribute to the broader internal and external scientific community through publications, talks, and technical artifacts. About the team Amazon’s third-party marketplace is a multibillion-dollar global service, connecting customers and sellers across through billions of transactions annually. The Seller Fee Science Team integrates economic modeling, machine learning, and artificial intelligence to guide business fee strategy, ensure fees are accurately computed for millions of products, and improve the seller experience with AI tools that support any fee related contact (understanding, audit, and dispute). We build the scientific foundation that empowers sellers to grow their businesses with clarity and confidence. Our team brings together world-class economists, physicists, mathematicians, and computer scientists to tackle diverse challenging problems that require theoretical rigor and deliver real-world impact.
Director, Applied Science, Full Funnel Advertising (FAIM)
US, CA, Palo Alto
We're seeking an Applied Science leader to build AI/ML-powered agentic systems that operate across the full advertising funnel, from awareness through conversion, autonomously optimizing advertiser outcomes at scale. You'll lead a world-class science and engineering team that ships production systems leveraging models and multi-agent architectures, transforming how millions of customers discover products and how advertisers engage with Amazon Ads powered by AI. You'll set the bar for technical excellence and high-velocity innovation: attract and retain top talent, maintain operational excellence, and ensure research translates into measurable, customer-centric impact. Key job responsibilities * Lead the development and implementation of generative AI strategies for Full funnel campaigns and New product campaigns * Drive technical strategy and roadmap decisions that balance innovation, scalability, and customer impact * Drive the architecture and delivery of production-grade multi-agent systems, including planning agents, bidding agents, creative agents, and measurement agents * Collaborate with cross-functional teams to integrate advanced AI technologies into existing advertising platforms * Spearhead research and innovation in AI-powered advertising solutions * Build and develop cross-functional teams of applied scientists and engineers * Make critical build-vs-buy and architectural tradeoff decisions across the agentic stack A day in the life Your day will be a dynamic blend of strategic leadership, technical innovation, and collaborative problem-solving. You'll work closely with cross-functional teams to design and implement advanced AI technologies that enhance advertising experiences, driving meaningful connections between brands and customers. About the team We are a passionate group of innovators dedicated to developing AI powered advertiser products that balance the needs of advertisers and enhance the user experience. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
Quantum Applied Scientist, Processor Test & Measurement, Amazon Center for Quantum Computing
US, CA, Pasadena
The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire an Applied Scientist in the Processor Test and Measurement group. You will join a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers working at the forefront of quantum computing. This role focuses on the verification and validation of the circuit components that make up a quantum error correction (QEC) code — such as gates, reset, and readout — and on understanding how the performance of those components contributes to overall QEC performance. We are looking for someone who enjoys connecting component-level measurements to integrated system behavior, and who is motivated by working across teams to understand it. Much of the work involves partnering with processor design, theory, and QEC colleagues to validate that new devices behave as their Hamiltonians predict, and to explore the gaps when they don't. A comfort with error budgeting — reasoning about where component performance comes from and what limits it — is central to the role. Candidates with a track record of original scientific contributions will be preferred. We value strong engineering principles, resourcefulness, problem solving, and clear communication, along with the ability to work effectively within a team. As an Applied Scientist you will have the opportunity to pursue new ideas and stay abreast of the field of experimental quantum computation. Key job responsibilities We are looking to hire an Applied Scientist to help verify and validate the circuit components of our error-corrected quantum processors and to understand how their performance maps to QEC requirements. Depending on background and interest, the work may include: - Collaborating with theory and processor design teams to develop experimental test plans that validate new processor designs and check that fabricated devices meet their intent. - Characterizing the building blocks of a QEC code and building error budgets that explain and bound their performance. - Designing experiments that help separate effects such as crosstalk and spectator interactions from intrinsic component performance. - Prototyping calibration and measurement approaches that can later be matured for automated, large-scale processor bring-up and QEC demonstrations. - Investigating discrepancies between measured and expected behavior, and feeding what you learn back into design and theory. You will have the opportunity to take part in high-impact research projects that intersect with our engineering roadmap, working closely with processor, theory, and QEC stakeholders so that component-level decisions are informed by overall system performance. A day in the life About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.
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