Amazon Nova AI Challenge: Trusted Software Agents, Rules

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.

IN, KA, Bengaluru
RBS (Retail Business Services) Tech team works towards enhancing the customer experience (CX) and their trust in product data by providing technologies to find and fix Amazon CX defects at scale. Our platforms help in improving the CX in all phases of customer journey, including selection, discoverability & fulfilment, buying experience and post-buying experience (product quality and customer returns). The team also develops GenAI platforms for automation of Amazon Stores Operations. As a Sciences team in RBS Tech, we focus on foundational ML research and develop scalable state-of-the-art ML solutions to solve the problems covering customer experience (CX) and Selling partner experience (SPX). We work to solve problems related to multi-modal understanding (text and images), task automation through multi-modal LLM Agents, supervised and unsupervised techniques, multi-task learning, multi-label classification, aspect and topic extraction for Customer Anecdote Mining, image and text similarity and retrieval using NLP and Computer Vision for product groupings and identifying duplicate listings in product search results. Key job responsibilities As an Applied Scientist, you will be responsible to design and deploy scalable GenAI, NLP and Computer Vision solutions that will impact the content visible to millions of customer and solve key customer experience issues. You will develop novel LLM, deep learning and statistical techniques for task automation, text processing, image processing, pattern recognition, and anomaly detection problems. You will define the research and experiments strategy with an iterative execution approach to develop AI/ML models and progressively improve the results over time. You will partner with business and engineering teams to identify and solve large and significantly complex problems that require scientific innovation. You will independently file for patents and/or publish research work where opportunities arise. The RBS org deals with problems that are directly related to the selling partners and end customers and the ML team drives resolution to organization level problems. Therefore, the Applied Scientist role will impact the large product strategy, identifies new business opportunities and provides strategic direction which is very exciting.
IN, KA, Bengaluru
Selection Monitoring team is responsible for making the biggest catalog on the planet even bigger. In order to drive expansion of the Amazon catalog, we develop advanced ML/AI technologies to process billions of products and algorithmically find products not already sold on Amazon. We work with structured, semi-structured and Visually Rich Documents using deep learning, NLP and image processing. The role demands a high-performing and flexible candidate who can take responsibility for success of the system and drive solutions from research, prototype, design, coding and deployment. We are looking for Applied Scientists to tackle challenging problems in the areas of Information Extraction, Efficient crawling at internet scale, developing ML models for website comprehension and agents to take multi-step decisions. You should have depth and breadth of knowledge in text mining, information extraction from Visually Rich Documents, semi structured data (HTML) and advanced machine learning. You should also have programming and design skills to manipulate Semi-Structured and unstructured data and systems that work at internet scale. You will encounter many challenges, including: - Scale (build models to handle billions of pages), - Accuracy (requirements for precision and recall) - Speed (generate predictions for millions of new or changed pages with low latency) - Diversity (models need to work across different languages, market places and data sources) You will help us to - Build a scalable system which can algorithmically extract information from world wide web. - Intelligently cluster web pages, segment and classify regions, extract relevant information and structure the data available on semi-structured web. - Build systems that will use existing Knowledge Base to perform open information extraction at scale from visually rich documents. Key job responsibilities - Use AI, NLP and advances in LLMs/SLMs and agentic systems to create scalable solutions for business problems. - Efficiently Crawl web, Automate extraction of relevant information from large amounts of Visually Rich Documents and optimize key processes. - Design, develop, evaluate and deploy, innovative and highly scalable ML models, esp. leveraging latest advances in RL-based fine tuning methods like DPO, GRPO etc. - Work closely with software engineering teams to drive real-time model implementations. - Establish scalable, efficient, automated processes for large scale model development, model validation and model maintenance. - Lead projects and mentor other scientists, engineers in the use of ML techniques. - Publish innovation in research forums.
US, MA, Boston
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON WEB SERVICES, INC. Offered Position: Data Scientist III Job Location: Boston, Massachusetts Job Number: AMZN9674163 Position Responsibilities: Own the data science elements of various products to help with data-based decision making, product performance optimization, and product performance tracking. Work directly with product managers to help drive the design of the product. Work with Technical Product Managers to help drive the build planning. Translate business problems and products into data requirements and metrics. Initiate the design, development, and implementation of scientific analysis projects or deliverables. Own the analysis, modelling, system design, and development of data science solutions for products. Write documents and make presentations that explain model/analysis results to the business. Bridge the degree of uncertainty in both problem definition and data scientific solution approaches. Build consensus on data, metrics, and analysis to drive business and system strategy. Position Requirements: Master's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science or a related field and two years of experience in the job offered or a related occupation. Employer will accept a Bachelor's degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master's degree and two years of experience. Must have one year of experience in the following skills: (1) building statistical models and machine learning models using large datasets from multiple resources; (2) building complex data analyses by leveraging scripting languages including Python, Java, or related scripting language; and (3) communicating with users, technical teams, and management to collect requirements, evaluate alternatives, and develop processes and tools to support the organization. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $161,803/year to $215,300/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000
US, CA, Palo Alto
About Sponsored Products and Brands 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. Key job responsibilities As a Machine Learning Applied Scientist, you will: * Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities * Develop scalable and effective machine-learning models and optimization strategies to solve business problems * Run regular A/B experiments, gather data, and perform statistical analysis * Work closely with software engineers to deliver end-to-end solutions into production * Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving * Conduct research on new machine-learning modeling and Generative AI solutions to optimize all aspects of Sponsored Products and Brands business About the team The Ad Response Prediction team within Sponsored Products and Brands (SPB) drives personalized shopping experiences for SPB Ads across placements, pages, and devices worldwide. We achieve this through ML and GenAI solutions that include customized shopper response prediction and session-level understanding to optimize every stage of the ad-serving process, from sourcing and bidding to widget discovery and auctions. Our responsibilities include advancing response prediction through model and feature innovations and extending prediction beyond the auction stage to areas such as targeting, sourcing, and bidding.
US, NY, New York
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the extreme. We focus on creating entirely new products and services with a goal of positively impacting the lives of our customers. No industries or subject areas are out of bounds. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have thirteen employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We are constantly learning through programs that are local, regional, and global. 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 highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best. Key job responsibilities - Lead and execute complex, ambiguous research projects from ideation to production deployment - Drive technical strategy and roadmap decisions for ML/AI initiatives - Collaborate cross-functionally with product, engineering, and business teams to translate research into scalable products - Publish research findings at top-tier conferences and contribute to the broader scientific community - Establish best practices for ML experimentation, evaluation, and deployment
US, CA, Santa Clara
We are seeking an Applied Scientist II to join Amazon Customer Service's Science team, where you will build AI-based automated customer service solutions using state-of-the-art techniques in retrieval-augmented generation (RAG), agentic AI, and post-training of large language models. You will work at the intersection of research and production, developing intelligent systems that directly impact millions of customers while collaborating with scientists, engineers, and product managers in a fast-paced, innovative environment. Key job responsibilities - Design, develop, and deploy information retrieval systems and RAG pipelines using embedding models, reranking algorithms, and generative models to improve customer service automation - Conduct post-training of large language models using techniques such as Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Group Relative Policy Optimization (GRPO) to optimize model performance for customer service tasks - Build and curate high-quality datasets for model training and evaluation, ensuring data quality and relevance for customer service applications - Design and implement comprehensive evaluation frameworks, including data curation, metrics development, and methods such as LLM-as-a-judge to assess model performance - Develop AI agents for automated customer service, understanding their advantages and common pitfalls, and implementing solutions that balance automation with customer satisfaction - Independently perform research and development with minimal guidance, staying current with the latest advances in machine learning and AI - Collaborate with cross-functional teams including engineering, product management, and operations to translate research into production systems - Publish findings and contribute to the broader scientific community through papers, patents, and open-source contributions - Monitor and improve deployed models based on real-world performance metrics and customer feedback A day in the life As an Applied Scientist II, you will start your day reviewing metrics from deployed models and identifying opportunities for improvement. You might spend your morning experimenting with new post-training techniques to improve model accuracy, then collaborate with engineers to integrate your latest model into production systems. You will participate in design reviews, share your findings with the team, and mentor junior scientists. You will balance research exploration with practical implementation, always keeping the customer experience at the forefront of your work. You will have the autonomy to drive your own research agenda while contributing to team goals and deliverables. About the team The Amazon Customer Service Science team is dedicated to revolutionizing customer support through advanced AI and machine learning. We are a diverse group of scientists and engineers working on some of the most challenging problems in natural language understanding and AI automation. Our team values innovation, collaboration, and a customer-obsessed mindset. We encourage experimentation, celebrate learning from failures, and are committed to maintaining Amazon's high bar for scientific rigor and operational excellence. You will have access to world-class computing resources, massive datasets, and the opportunity to work alongside some of the brightest minds in AI and machine learning.
US, CA, Sunnyvale
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine innovative AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. We leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. We are pioneering the development of robotics foundation models that: - Enable unprecedented generalization across diverse tasks - Integrate multi-modal learning capabilities (visual, tactile, linguistic) - Accelerate skill acquisition through demonstration learning - Enhance robotic perception and environmental understanding - Streamline development processes through reusable capabilities The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. As a Senior Applied Scientist, you will develop and improve machine learning systems that help robots perceive, reason, and act in real-world environments. You will leverage state-of-the-art models (open source and internal research), evaluate them on representative tasks, and adapt/optimize them to meet robustness, safety, and performance needs. You will invent new algorithms where gaps exist. You’ll collaborate closely with research, controls, hardware, and product-facing teams, and your outputs will be used by downstream teams to further customize and deploy on specific robot embodiments. Key job responsibilities As a Senior Applied Scientist in the Foundations Model team, you will: - Leverage state-of-the-art models for targeted tasks, environments, and robot embodiments through fine-tuning and optimization. - Execute rapid, rigorous experimentation with reproducible results and solid engineering practices, closing the gap between sim and real environments. - Build and run capability evaluations/benchmarks to clearly profile performance, generalization, and failure modes. - Contribute to the data and training workflow: collection/curation, dataset quality/provenance, and repeatable training recipes. - Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs - Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions. - Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.
US, CA, Sunnyvale
Amazon's AGI Information is seeking an exceptional Applied Scientist to drive science advancements in the Amazon Knowledge Graph team (AKG). AKG is re-inventing knowledge graphs for the LLM era, optimizing for LLM grounding. At the same time, AKG is innovating to utilize LLMs in the knowledge graph construction pipelines to overcome obstacles that traditional technologies could not overcome. As a member of the AKG IR team, you will have the opportunity to work on interesting problems with immediate customer impact. The team is addressing challenges in web-scale knowledge mining, fact verification, multilingual information retrieval, and agent memory operating over Graphs. You will also have the opportunity to work with scientists working on the other challenges, and with the engineering teams that deliver the science advancements to our customers. A successful candidate has a strong machine learning and agent background, is a master of state-of-the-art techniques, has a strong publication record, has a desire to push the envelope in one or more of the above areas, and has a track record of delivering to customers. The ideal candidate enjoys operating in dynamic environments, is self-motivated to take on new challenges, and enjoys working with customers, stakeholders, and engineering teams to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems. You will collaborate with applied scientists and engineers to develop novel algorithms and modeling techniques to build the knowledge graph that delivers fresh factual knowledge to our customers, and that automates the knowledge graph construction pipelines to scale to many billions of facts. Your first responsibility will be to solve entity resolution to enable conflating facts from multiple sources into a single graph entity for each real world entity. You will develop generic solutions that work fo all classes of data in AKG (e.g., people, places, movies, etc.), that cope with sparse, noisy data, that scale to hundreds of millions of entities, and that can handle streaming data. You will define a roadmap to make progress incrementally and you will insist on scientific rigor, leading by example.
US, MA, N.reading
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models. At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence. The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment. Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration. Key job responsibilities - Design and implement whole body control methods for balance, locomotion, and dexterous manipulation - Utilize state-of-the-art in methods in learned and model-based control - Create robust and safe behaviors for different terrains and tasks - Implement real-time controllers with stability guarantees - Collaborate effectively with multi-disciplinary teams to co-design hardware and algorithms for loco-manipulation - Mentor junior engineer and scientists
CN, 31, Shanghai
As a Sr. Applied Scientist, you will be responsible for bringing new product designs through to manufacturing. You will work closely with multi-disciplinary groups including Product Design, Industrial Design, Hardware Engineering, and Operations, to drive key aspects of engineering of consumer electronics products. In this role, you will use expertise in physical sciences, theoretical, numerical or empirical techniques to create scalable models representing response of physical systems or devices, including: * Applying domain scientific expertise towards developing innovative analysis and tests to study viability of new materials, designs or processes * Working closely with engineering teams to drive validation, optimization and implementation of hardware design or software algorithmic solutions to improve product and customer risks * Establishing scalable, efficient, automated processes to handle large scale design and data analysis * Conducting research into use conditions, materials and analysis techniques * Tracking general business activity including device health in field and providing clear, compelling reports to management on a regular basis * Developing, implementing guidelines to continually optimize design processes * Using simulation tools like LS-DYNA, and Abaqus for analysis and optimization of product design * Using of programming languages like Python and Matlab for analytical/statistical analyses and automation * Demonstrating strong understanding across multiple physical science domains, e.g. structural, thermal, fluid dynamics, and materials * Developing, analyzing and testing structural solutions from concept design, feature development, product architecture, through system validation * Supporting product development and optimization through application of analysis and testing of complex electronic assemblies using advanced simulation and experimentation tools and techniques