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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.

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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.

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Applied Scientist II, Sponsored Products Global Optimization
US, CA, Palo Alto
Global Optimization is a strategic initiative aimed at improving Amazon advertisers experience at global scale. We are looking for a passionate Applied Scientist to help pioneer the next generation of agentic AI applications for Amazon advertisers. In this role, you will design agentic architectures, develop tools and datasets, and contribute to building systems that can reason, plan, and act autonomously across complex advertiser workflows at global scale. You will work at the forefront of applied AI, developing methods for fine-tuning, reinforcement learning, and preference optimization, while helping create evaluation frameworks that ensure safety, reliability, and trust at scale. You will work backwards from the needs of advertisers—delivering customer-facing products that directly help them create, optimize, and grow their campaigns. Beyond building models, you will advance the agent ecosystem by experimenting with and applying core primitives such as tool orchestration, multi-step reasoning, and adaptive preference-driven behavior. This role requires working independently on ambiguous technical problems, collaborating closely with scientists, engineers, and product managers to bring innovative solutions into production. Key job responsibilities - Design and build agents that improve advertisers experiences globally - Design and implement advanced model and agent optimization techniques, including supervised fine-tuning, instruction tuning and preference optimization (e.g., DPO/IPO). - Design and implement optimization models that work at global scale taking into account nuances of multiple countries - Innovate new science models to help advertisers scale their campaigns globally - Curate datasets and tools for MCP. - Build evaluation pipelines for agent workflows, including automated benchmarks, multi-step reasoning tests, and safety guardrails. - Develop agentic architectures (e.g., CoT, ToT, ReAct) that integrate planning, tool use, and long-horizon reasoning. - Prototype and iterate on multi-agent orchestration frameworks and workflows. - Collaborate with peers across engineering and product to bring scientific innovations into production. - Stay current with the latest research in LLMs, RL, and agent-based AI, optimization and translate findings into practical applications. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest 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. The Global Optimization team within Sponsored Products and Brands is focused on guiding and supporting 1.6MM advertisers to meet their advertising needs of creating and managing ad campaigns at global scale. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in guidance systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our work is grounded in state-of-the-art agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning, MCP, and preference optimization), ensuring our systems are both scalable and adaptive.
Senior Research Scientist, Industrial Robotics Group
US, WA, Seattle
Amazon is seeking exceptional science talent to develop AI and machine learning systems that will enable the next generation of advanced manufacturing capabilities at unprecedented scale. We're building revolutionary software infrastructure that combines cutting-edge AI, large-scale optimization, and advanced manufacturing processes to create adaptive production control systems. As a Senior Research Scientist, you will develop and improve machine learning systems that enable real-time manufacturing flow decisions. You will leverage state-of-the-art optimization and ML techniques, evaluate them against representative manufacturing scenarios, and adapt them to meet the robustness, reliability, and performance needs of production environments. You will invent new algorithms where gaps exist. You'll collaborate closely with software engineering, manufacturing engineering, robotics simulation, and operations teams, and your outputs will directly power the systems that determine what to build next, where to allocate resources, and how to maximize throughput. The ideal candidate brings deep expertise in optimization and machine learning, with a proven track record of delivering scientifically complex solutions into production. You are hands-on, writing significant portions of critical-path scientific code while driving your team's scientific agenda. If you're passionate about inventing the intelligent manufacturing systems of tomorrow rather than optimizing those of today, this role offers the chance to make a lasting impact on the future of automation. Key job responsibilities - Identify and devise new scientific approaches for constraint identification, dispatch optimization, WIP release control, and predictive flow intelligence when the problem is ill-defined and new methodologies need to be invented - Lead the design, implementation, and successful delivery of scientifically complex solutions for real-time manufacturing flow optimization in production - Design and build ML models and optimization algorithms including constraint prediction, starvation risk forecasting, and dispatch optimization - Write a significant portion of critical-path scientific code with solutions that are inventive, maintainable, scalable, and extensible - Execute rapid, rigorous experimentation with reproducible results, closing the gap between simulation and real manufacturing environments - Build evaluation benchmarks that measure model performance against manufacturing outcomes including constraint utilization and throughput rather than traditional ML metrics alone - Influence your team's science and business strategy through insightful contributions to roadmaps, goals, and priorities - Partner with manufacturing engineering, robotics simulation, and applied intelligence teams to ensure scientific approaches are grounded in operational reality - Drive your team's scientific agenda and role model publishing of research results at peer-reviewed venues when appropriate and not precluded by business considerations - Actively participate in hiring and mentor other scientists, improving their skills and ability to deliver - Write clear narratives and documentation describing scientific solutions and design choices
Senior Applied Scientist
US, WA, Seattle
At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product identity and relationships at unprecedented scale. Using Generative AI, Visual Language Models (VLMs), and multimodal reasoning, we determine what makes each product unique and how products relate to one another across Amazon's catalog. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity—from electronics to groceries to digital content. The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Establishing product identities and groupings requires sophisticated models that reason across text, images, and structured data—while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily. Amazon's Item and Relationship Platform group is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers. Key job responsibilities Key job responsibilities include: * Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval—translating ambiguous business challenges into tractable scientific frameworks * Design and implement leading models leveraging VLMs, foundation models, and agentic architectures to solve product identity, relationship inference, and catalog understanding at billion-product scale * Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions * Own end-to-end ML pipelines from research ideation to production deployment—processing petabytes of multimodal data with rigorous evaluation frameworks * Define research roadmaps aligned with business priorities, balancing foundational research with incremental product improvements * Mentor peer scientists and engineers on advanced ML techniques, experimental design, and scientific rigor—building organizational capability in GenAI and multimodal AI * Represent the team in the broader science community—publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research
Research Scientist , Trustworthy Shopping Experience (TSE)
IN, KA, Bengaluru
Are you passionate about solving complex business problems at scale through Generative AI? Do you want to help build intelligent systems that reason, act, and learn from minimal supervision? If so, we have an exciting opportunity for you on Amazon's Trustworthy Shopping Experience (TSE) team. At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy. We do this in close partnership with our selling partners, empowering them with best-in-class tools and expertise to offer a high-quality, compliant selection that customers trust. As a Research Scientist I, you will bring subject matter expertise with fundamental improvements in at least one relevant discipline (e.g., NLP, computer vision, representation learning, agentic architecture) to contribute to next-generation agentic AI solutions that automate complex manual investigation processes at Amazon scale. You will invent, refine, and experiment with solutions spanning agentic reasoning, self-supervised representation learning, few-shot adaptation, multimodal understanding, and model compression. With guidance from senior scientists, you will stay current on research trends and benchmark your results against the state of the art. You will help design and execute experiments to identify optimal solutions, initiating the development and implementation of small components with team guidance. You will write secure, stable, testable, and well-documented production code at the level of an SDE I, rigorously evaluating models and quantifying performance. You will handle data in accordance with Amazon policies, troubleshoot issues to root cause, and ensure your work does not put the company at risk. Your scope of influence will typically be at the self-level, with the possibility of mentoring interns. You will participate in team design and prioritization discussions, learn the business context behind TSE's products, and escalate problems with proposed solutions. You will publish internal technical reports and may contribute to peer-reviewed publications and external review activities when aligned with business needs. This role offers a unique opportunity to contribute to end-to-end AI development—from research through production—with your contributions serving hundreds of millions of customers within months, not years. Key job responsibilities • Contribute to the design and development of agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence, including feedback and memory mechanisms, leveraging reinforcement learning techniques for agent decision-making and policy optimization, with input and guidance from senior scientists • Develop novel models built on top of SFT (Supervised Fine-tuning) and RFT (Reinforced Fine-tuning) approaches, as well as few-shot approaches based on multimodal datasets spanning text, images, and structured data, applying mathematical optimization techniques to improve efficiency, resource allocation, and decision-making in complex workflows, working alongside senior scientists to identify optimal solutions • Contribute to building production-ready deep learning and conventional ML solutions, including multimodal fusion and cross-modal alignment techniques that seamlessly connect visual, textual, and relational understanding, to support automation requirements within your team's scope • Help identify customer and business problems; use reasonable assumptions, data, and customer requirements to solve well-defined scientific problems involving multimodal inputs such as unstructured text, documents, product images, and relational data, developing representations that capture complementary signals across modalities and mapping business goals to scientific metrics • May co-author research papers for peer-reviewed internal and/or external venues, including contributions in areas such as multimodal representation learning and vision-language modeling, and contribute to the wider scientific community by reviewing research submissions, when aligned with business needs • Prototype rapidly, iterate based on feedback, and deliver small components at SDE I level—including multimodal data pipelines and inference modules—that integrate into production-scale systems • Write secure, stable, testable, maintainable, and well-documented code, balancing model capability, deployment cost, and resource usage across multimodal architectures while understanding state-of-the-art data structures, algorithms, and performance tradeoffs • Rigorously test code and evaluate models across individual and combined modalities, quantifying their performance; troubleshoot issues, research root causes, and thoroughly resolve defects, leaving systems more maintainable • Participate in team design, scoping, and prioritization discussions through clear verbal and written communication; seek to learn the business context, science, and engineering behind your team's products, including how multimodal signals contribute to trust and safety decisions • Participate in engineering best practices with peer reviews; clearly document approaches and communicate design decisions; publish internal technical reports to institutionalize scientific learning • Help train and mentor scientist interns; identify and escalate problems with proposed solutions, taking ownership or ensuring clear hand-off to the right owner
Applied Scientist, Ads Science and Analysis Team
US, NY, New York
We are seeking a scientist to further the development and application of analytics methods to examine the complex data flows of Amazon Ads and to translate deep-dives into actionable insights for our product teams. In this role you will develop new tools to analyze our advertising data to help improve the performance of our bidding algorithms, targeting and relevance systems, help advance our supply strategy, and evaluate the adoption and impact of feature releases. Key job responsibilities - Analyze data trends regarding supply, optimization, ad load, and advertising mix effects that affect advertiser performance and contribute to achieving advertiser goals - Present papers to senior leaders on issues like feature development impact on identity recognition rates, and changes of ad selection systems to improve fill rate highlighting insights that will inform our business development and engineering roadmaps - Formalize our analytics approach to Ads auctions by analyzing bid spreads, auction depth, and simulating impacts of potential auction structure changes - Identify, standardize, and operationalize KPIs to effectively measure the performance of all systems involved in ad serving, and use trend insights to inform business priorities - Partner with engineering teams to define data logging requirements and getting these prioritized in engineering roadmaps - Validate financial models through analysis - Develop and own ad revenue and supply intelligence analytics decks that provide ongoing deep-dives A day in the life The Ads Scientist will work closely with business leaders and engineers on developing common data architecture that will optimize our data logging at different grains, and will allow data interoperability from bid flow to optimization to campaign delivery. The scientist will then analyze the data and present papers and ongoing reports on actionable insights. About the team At Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work. Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.
Economist, People Experience and Technology Central Science
US, VA, Arlington
The People eXperience and Technology Central Science (PXTCS) team uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. The Benefits Science team is looking for an economist to transform complex business challenges into actionable scientific insights. In this role, you will partner directly with business leaders to design and evaluate pilots, build models using large-scale data, and scale successful prototypes into company-wide policies and programs. We're looking for someone who can combine rigorous scientific thinking with practical business acumen and is passionate about using economics to improve employee experiences at scale. The ideal candidate will thrive in interdisciplinary environments, working alongside engineers, data scientists, and business leaders from diverse backgrounds. Key job responsibilities - Design and conduct rigorous evaluations of benefits programs - Support the development and application of structural models - Develop experiments to evaluate the impact of benefits initiatives - Communicate complex findings to business stakeholders in clear, actionable terms - Work with engineering teams to develop scalable tools that automate and streamline evaluation processes A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions.
Principal Economist, Ads Econ
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Our products are used daily to surface new selection and provide customers a wider set of product choices along their shopping journeys. The business is focused on generating value for shoppers as well as advertisers. Our team uses a combination of econometrics, machine learning, and data science to build disruptive products for all our Advertising products. We also generate insights to guide Amazon Advertising strategy, providing direct support to senior leadership. We are looking for an experienced Economist who have a deep passion for building state-of-art causal models and ads measurement and optimization solutions, ability to communicate data insights and scientific vision, and execute strategic projects. As an Economist on this team, you will: - Lead the design and analysis of large-scale experiments to measure advertising effectiveness across Amazon's advertising products - Develop novel causal inference and econometric methodologies to solve attribution and incrementality measurement challenges at scale - Invent new optimization frameworks that translate measurement insights into actionable bidding, targeting, and budget allocation strategies for advertisers - Define the long-term science roadmap for ads measurement and optimization, identifying high-impact research directions and driving alignment across engineering, product, and science teams - Build and refine structural and reduced-form models that quantify the causal impact of advertising on consumer behavior, sales, and brand outcomes - Partner with engineering teams to operationalize econometric models into production systems serving millions of advertisers - Mentor and develop a team of economists and applied scientists, raising the bar on methodological rigor and scientific impact - Influence senior leadership through clear communication of complex economic concepts, shaping investment decisions and product strategy - Collaborate cross-functionally with product managers, engineers, and business leaders to translate business problems into well-defined economic questions with scalable solutions Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.
Principal Data Scientist, Prime Video
US, WA, Seattle
Interested in influencing what customers around the world see when they turn on Prime Video? The Prime Video Personalization and Discovery team matches customers with the right content at the right time, at all touch points throughout the content discovery journey. We are looking for a customer-focused, solutions-oriented Principal Data Scientist to develop next-gen measurement and experimentation systems within Prime Video Personalization and Discovery. You'll be part of an embedded science team driving projects across product and engineering teams that ultimately influence what millions of customers around the world see when the log into Prime Video. The ideal candidate brings experience building experiment-based measurement systems at scale, excellent stakeholder communication skills, and the ability to balance technical rigor with delivery speed and customer impact. You will build cross-functional support within Prime Video for high-quality, rigorous measurement, assess business problems, and support iterative scientific solutions that balance short-term delivery with long-term science roadmaps. Key job responsibilities - Define and drive the multi-year vision for experiment-based measurement systems within Prime Video - Partner with product stakeholders and science peers to identify strategic data-driven opportunities to improve the customer experience - Communicate findings, conclusions, and recommendations to technical and non-technical business leaders across Prime Video - Educate senior leaders about and advocate for high-quality measurement as an input to data-driven decisions - Mentor junior scientists and review technical artifacts to ensure quality - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organization
Research Scientist, WWGS Real Estate & Store Development
US, WA, Seattle
Do you want to help shape the future of Amazon's physical retail presence? Worldwide Grocery Stores (WWGS), Location Strategy and Analytics team is looking for an Research Scientist to join us in developing advanced forecasting models, optimization models, and analytical tools to support critical real estate and store planning decisions for Amazon's Worldwide Grocery business, including Whole Foods Market. Our team is responsible for developing predictive models and tools to support Real Estate and Topology analysts in making important decisions regarding our stores—including new store openings, relocations, closures, remodels, design, new formats, and more. We leverage statistical modeling, machine learning, and GenAI to build solutions for store sales forecasting, sales transfer effects, macrospace optimization, store network optimization, store network diffusion planning, and causal effects. As a Research Scientist on our team, you will apply your technical and analytical skills to tackle complex business problems and develop innovative solutions to improve our forecasting and decision-making capabilities. You will collaborate with a diverse team of scientists, economists, and business partners to identify opportunities, develop hypotheses, build internal products, and translate analytical insights into actionable recommendations for Executive Leadership. Key job responsibilities - Design and implement forecasting models and machine learning solutions to predict store performance and optimize our retail network. - Analyze large datasets to uncover insights and patterns related to store performance, customer behavior, and market dynamics. - Develop end-to-end solutions, tools and frameworks to scale our ML model development and data analysis. - Leverage GenAI models to enhance user interaction with our solutions, improve overall user experience, and build new features. - Present research findings and recommendations to scientists, business leaders, and executives. - Collaborate with cross-functional teams to drive adoption of models and insights. - Stay current on latest developments in relevant fields and propose innovative approaches. About the team We are a team of scientists passionate about leveraging data and advanced analytics to drive strategic decisions for Amazon's grocery business. Our work directly impacts Amazon's worldwide grocery store growth and development strategy. We foster a collaborative environment where team members are encouraged to think creatively, challenge assumptions, and pursue novel approaches to solving complex problems. Our team is at the forefront of applying a multitude of techniques - including GenAI - to improve our scientific solutions and products.
Data Scientist II, SCOT OSS - Sourcing Execution & Performance
US, WA, Bellevue
Have you ever ordered a product on Amazon and when that box with the smile arrived, wondered how it got to you so fast? Wondered where it came from and how much it cost Amazon? If so, the Amazon Global Supply Chain Optimization Technology (SCOT) organization is for you. Watch this video to learn more about our organization, SCOT: http://bit.ly/amazon-scot We are the Optimal Sourcing Systems team (OSS) within SCOT and are looking for a Data Scientist II to join us! OSS designs and builds systems that measure and manage Amazon’s supplier capabilities, identify and react to supply disruptions, and prioritizes inbound freight for our global network. OSS software is used by every country Amazon services, and is a critical link to ensuring Amazon offers the products our customers want, at the lowest possible cost. This team under OSS orchestrates and tracks inventory movement into Amazon's network, maintains performance feedback loops, and ensures vendor compliance. The Data Scientist II, in partnership with the Product Management, Operations, and Tech teams, will lead efforts in four areas: 1) Building models to set optimal parameters such as lead times to ensure the accuracy of our Inbound network 2) Building analytical frameworks to identify and drive improvements in purchase order lifecycle management and defect coaching/chargebacks 3) Developing Gen AI solutions related to dispute evaluation and vendor coaching 4) Building models and solutions to enable collaborative inventory planning with vendors The ideal candidate thrives in ambiguous problem spaces, relishes working with large volumes of data, and enjoys the challenge of highly complex supply chain contexts. They can translate complex business logic into scalable models and communicate insights effectively to both technical and non-technical stakeholders. Keys to success in this role include exceptional analytics, statistics, judgment, and communication skills. Experience with supply chain optimization, operations research, or vendor management systems is a plus. Key job responsibilities - Collaborate with product managers, science, and engineering teams to design and implement model solutions for Sourcing Execution & Performance systems - Use large datasets or experiments to make causal inferences or predictions - Work with engineers to automate science analysis processes and build scalable measurement solutions - Interpret data, write reports, and make actionable recommendations - Drive technical standards and best practices for the team's Science solutions - Mentor and provide technical guidance to other team members on complex projects A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: - Medical, Dental, and Vision Coverage - Maternity and Parental Leave Options - Paid Time Off (PTO) - 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
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