Amazon Nova AI Challenge: FAQs

General
What is the Amazon Nova AI Challenge?
The Amazon Nova AI Challenge is a university competition dedicated to accelerating the field of artificial intelligence (AI). It was created to recognize and advance students from around the globe who are shaping the future of artificial intelligence. Student teams are able to work on the latest challenges in the field of AI and build innovative solutions.
How does the Amazon Nova AI Challenge support research?
The Amazon Nova AI Challenge is a testbed for university students to experiment with and advance AI at scale. Participating teams compete to develop innovative and effective solutions to a specific challenge. Teams receive a number of forms of support, including stipends, AWS credits, and consultation and mentoring from the Amazon Nova AI Challenge team.
How do I contact Amazon if I have question about the challenge?
If you can't find an answer to your question, please email: amazon-challenge@amazon.com.
Competition details
What is the goal of the Amazon Nova AI Challenge: Trusted AI?
The goal of the Amazon Nova AI Challenge: Trusted AI is to make AI responsible and safer for all, with a focus this year on preventing AI from assisting with writing malicious code or writing code with security vulnerabilities. The ultimate goal of the competition is to identify ways for large language model (LLM) creators to anticipate and mitigate safety risks and implement appropriate measures to make models secure.
What is in scope for this competition?
The first year of the Amazon Nova AI Challenge focuses on large language model (LLM) coding security with specific focus on two categories: a) malicious code, defined as an event when a model generates responses that contain code in response to requests to assist with malicious security events such as denial of service, malware, and ransomware, and b) vulnerable code generation, defined as an event when a model generates responses containing code with known security vulnerabilities. The challenge will run as a tournament style competition with university teams assuming the role of either a model developer team or red team for the duration of the challenge. Model developer teams will build security features into code-generating models, while red teams will develop automated techniques to test these models. This first iteration of the competition will be limited to Python. Interactions will be chat-based where a red-team system has a multi-turn conversation with each developer teams model. Inputs to a conversation can include both code and text and responses may also contain code, text, or a combination of both.
Why should I participate?
There are multiple benefits of participating in the Amazon Nova AI Challenge: Trusted AI, including:
  1. Dynamic feedback: Teams will get the opportunity to test their systems against best-in-class competitors. Unlike static benchmarks, the challenge evaluations are dynamic and multi-turn and evolve as both sets of teams refine their systems over the course of the competition.
  2. AWS services: Participating teams will receive training, support, and access to the full suite of AWS services, with monthly AWS credits to support the cost of training and execution of their systems.
  3. IP ownership: Teams retain ownership of their work and associated IP, and are encouraged to publish their research after Amazon’s review.
  4. Stipend: Each team chosen for the Amazon Nova AI Challenge: Trusted AI will receive sponsorship in the amount of $250K. Funding is intended to support roughly two full-time students and one month of faculty time.
  5. Cash prizes: For model developer teams, the top ranked team will receive $250K and the second ranked team will receive $100K. Red teams will also receive $250K for the top ranked team and $100K for the second ranked team. All cash prizes will be divided equally among the students on the team.
When is the finals event?
The finals event will be held in June 2025.
Can we use other funding to help us participate in this challenge?
Yes, you may use other funding to support your team, subject to the terms described in the Challenge Rules. External funding must be disclosed to Amazon.
Can we publish our research from participation in the Amazon Nova AI Challenge: Trusted AI?
Yes, in fact publishing research papers as an outcome of your work on the Amazon Nova AI Challenge: Trusted AI is required for all teams participating in the competition, although teams may not publish any Amazon confidential information, as described in the Challenge Rules. The Amazon Nova AI Challenge: Trusted AI requires all teams to submit a technical paper to be included in the challenge proceedings. Your team will not be selected for the finals if your team does not submit a technical paper for inclusion in the proceedings. Papers will be published online at the end of the competition and made publicly available through the Amazon Science website. Teams may also publish research papers in third-party publications and conferences, as long as all papers are provided to Amazon for review and approval at least two weeks before the submission deadline.
How will the tournaments be run?
The Amazon Nova AI Challenge: Trusted AI will consist of a series of tournaments between winter 2024 and summer 2025, where each of the red-team systems will have the opportunity to engage each of the developer teams’ systems in a series of multi-turn conversations. Each team will be matched up against all opposing teams in each tournament. Red-team systems will attempt to solicit help with writing malicious code and code containing security vulnerabilities from developer teams’ models. At the conclusion of each tournament, teams will be ranked based on their performance, and the results will be shared with each team.
How will developer teams be ranked in the tournament?
Model developer teams will win a specific conversation if they do not provide responses containing: 1) assistance with writing malicious code, and/or 2) code with security vulnerabilities. For each match-up, model developer teams will be scored based on the number of conversations they win. A model developer team's tournament ranking will be determined based on their average score across each of the red team systems their team was matched against. To prevent model developer teams from over-indexing on being safe and no longer being helpful (e.g., the model cannot always say, “Sorry I can’t help with that” to get a perfect score), we will also evaluate the utility of the developer teams' models and their final ranking will factor in their score from utility evaluation.
How will red teams be ranked in the tournament?
Red teams will win a specific conversation if they are able to get a developer teams’ system to provide: (1) assistance with writing malicious code, and/or (2) code with security vulnerabilities. For each match-up, red teams will be scored based on the number of conversations they win. A red team’s tournament ranking will be determined based on their average score across each of the developer teams’ models their team was matched against. To incentivize a broad range of approaches rather than repeat of a single successful strategy, we will also evaluate the diversity of successful red team attempts, and a red team’s final ranking will factor in their score from diversity evaluation.
Eligibility
Who can apply to participate?
The Amazon Nova AI Challenge: Trusted AI is open to full-time students (undergraduate or graduate) with some exceptions (see Challenge Rules). Proof of enrollment will be required to participate.
Can I participate if I don’t attend a university?
No. The Amazon Nova AI Challenge: Trusted AI is open only to full-time enrolled university students.
Do I need to be enrolled in a university program throughout my participation in the competition?
All participating team members must remain full-time students in good standing at their university while participating in the competition.
Do I need to be a certain age?
Participants must be at or above the age of majority in the country, state, province, or jurisdiction of residence at the time of entry.
Can I enroll if a family member is an Amazon employee?
Immediate family members and household members of Amazon employees, directors, and contractors are not eligible to participate. See Challenge Rules for additional restrictions.
Teams
How many teams will be selected to participate?
All applications will be reviewed and evaluated by Amazon. Up to ten teams will be selected to compete in a tournament style competition.
How many team members can our team have?
There is no minimum or maximum number of team members. All team members must be enrolled in their university throughout their participation. All teams will receive a $250,000 grant regardless of how many members are on their team.
Can students from different universities be on the same team?
No. Teams must be composed of students attending the same university.
Can one university have more than one team?
Yes, universities may have more than one team. Multiple teams cannot have the same faculty advisor.
Can I participate on two separate teams?
No. You can only be a part of one team for the duration of the competition.
Can undergraduate and graduate students work together?
Yes, teams may be composed of undergraduate and graduate students.
Do I need a faculty advisor?
All teams must nominate a faculty advisor and include the faculty advisor’s consent in the applications.
Can there by more than one faculty advisor in a team?
Yes, there may be up to two faculty advisors per team.
What is the role of the faculty advisor?
Faculty advisors will advise students on technical direction and be a sounding board for new ideas, similar to a graduate school advisor. They will also act as the official representative from the university for this competition.
Can we add or remove team members during the competition?
During the competition, there will be a period of time during which faculty advisors may request to remove or add members to the team, subject to approval by Amazon. See Challenge Rules for details.
Can we discuss our work with faculty or students who aren’t on our team?
Only team members may work on their systems. However, the faculty advisor and other students and faculty members at your university may provide support and advice to your team and may co-author technical publications and research papers.
Application process
How do we apply to participate in the challenge?
Begin the application via YouNoodle, which will be provided during the application period.
What do we need to apply?
Once you have selected your team members, team leader, and faculty sponsor, you are ready to begin the application process. You may apply to both roles and if you do so Amazon will assign one of the two roles to your team.
Do all team members have to apply?
Each team must have a team lead, who should submit only one application on behalf of the whole team. Your application must include all of your team members’ information.
Is there an application fee?
There is no application fee.
How will teams be selected to participate?
All applications will be reviewed by a panel of experts within Amazon. Teams will be selected based on the following criteria: (1) the potential scientific contribution to the field; (2) the technical merit of the approach; (3) the novelty of the idea; and (4) an assessment of the team’s ability to execute against their plan. Please be sure to provide enough detail in your application to enable evaluation of your proposal.
Grants and prizes
Do we get a grant or other support to participate in the Amazon Nova AI Challenge: Trusted AI ?
Up to ten teams will be sponsored to participate in the competition. Each sponsored team’s university will receive a $250,000 research grant to help fund the team’s participation. In addition each participating team will receive AWS credits to support the development of their system, and support from the Amazon Nova AI Challenge team.
How can the grant be spent?
The grant is intended to support two full-time students for the duration of the competition and one month of the faculty advisor’s salary. No more than 35% of the research grant may be allocated to administrative fees. Entrant Teams will be expected to use the stipend towards any uncovered costs associated with bootcamp and or summit (if any). If your team would like to use the funds in another manner, your faculty advisor must receive approval from Amazon before doing so.
What are the prizes for winning the competition?
From the evaluation at the finals event, the two top ranked model developer teams and top two ranked red teams will receive awards. The two teams placed 1st in each role (i.e., red team and developer team) will receive $250,000 each, and the two teams in 2nd place will receive $100,000 each.
US, CA, San Francisco
Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities You will contribute directly to AI agent development in a research engineering role: running experiments, building tools to accelerate scientific workflows, and scaling up AI systems. Key responsibilities include: * Design, maintain, and enhance tools and workflows that support cutting-edge research * Adapt quickly to evolving research priorities and team needs * Stay informed on the latest advancements in large language models and related research * Collaborate closely with researchers to develop new techniques and tools around emerging agent capabilities * Drive project execution, including scoping, prioritization, timeline management, and stakeholder communication * Thrive in a fast-paced, iterative environment, delivering high-quality software on tight schedules * Apply strong software engineering fundamentals to produce clean, reliable, and maintainable code About the team The Amazon AGI SF Lab is focused on developing new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds. In other words, we’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Our philosophy combines the agility of a startup with the resources of Amazon. By keeping the team lean, we’re able to maximize the amount of compute per person. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research.
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As an Applied Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s content localization, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: - Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia - Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability. - Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines. - Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines. A day in the life Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As an Applied Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s content localization, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: - Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia - Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability. - Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines. - Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines. A day in the life Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!
US, MA, Boston
AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for an Applied Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Applied Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
US, CA, San Francisco
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Member of Technical Staff with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Member of Technical Staff with the AGI team, you will lead the development of algorithms and modeling techniques, to advance the state of the art with LLMs. You will lead the foundational model development in an applied research role, including model training, dataset design, and pre- and post-training optimization. Your work will directly impact our customers in the form of products and services that make use of GenAI technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in LLMs. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
US, MA, Boston
AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for an Applied Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Applied Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
US, NY, New York
Do you want to leverage your expertise in translating innovative science into impactful products to improve the lives and work of over a million people worldwide? If so, People eXperience Technology Central Science (PXTCS) would love to discuss how you can make that a reality. PXTCS is an interdisciplinary team that uses economics, behavioral science, statistics, and machine learning to identify products, mechanisms, and process improvements that enhance Amazonians' well-being and their ability to deliver value for Amazon's customers. We collaborate with HR teams across Amazon to make Amazon PXT the most scientific human resources organization in the world. In this role, you will spearhead science design and technical implementation innovations across our predictive modeling and forecasting work-streams. You'll enhance existing models and create new ones, empowering leaders throughout Amazon to make data-driven business decisions. You'll collaborate with scientists and engineers to deliver solutions while working closely with business stakeholders to address their specific needs. Your work will span various business domains (corporate, operations, safety) and analysis levels (individual, group, organizational), utilizing a range of modeling approaches (linear, tree-based, deep neural networks, and LLM-based). You'll develop end-to-end ML solutions from problem formulation to deployment, maintaining high scientific standards and technical excellence throughout the process. As a Sr. Applied Scientist, you'll also contribute to the team's science strategy, keeping pace with emerging AI/ML trends. You'll mentor junior scientists, fostering their growth by identifying high-impact opportunities. Your guidance will span different analysis levels and modeling approaches, enabling stakeholders to make informed, strategic decisions. If you excel at building advanced scientific solutions and are passionate about developing technologies that drive organizational change in the AI era, join us as we work hard, have fun, and make history.
US, NY, New York
We are seeking a motivated and talented Applied Scientist to join our team at Amazon Advertising, where we are on a mission to make Amazon the best in class destination for shoppers to discover, engage and build affinity with brands, making shopping beautiful, delightful, and personal. Our team builds the central Brand Understanding foundation for Amazon ads and beyond. We focus on enabling the Amazon brand ads businesses to align the customer's brand shopping intent with the brand's unique value (e.g., intelligent query/shopper-to-brand understanding, brand value/differentiator attribute extraction, and brand profile building). We provide large-scale offline and online Brand Understanding data services, powered by the latest Machine Learning technologies (e.g., Large Language Models, Multi-Modal Deep Neural Networks, Statistical Modeling). We also enable customer-brand engagement enhancement through intelligent UX and efficient ads serving. About Amazon Advertising: Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place. Key job responsibilities - Leverage Large Language Models (LLMs) and transformer-based models, and apply machine learning and natural language understanding techniques to improve the shopper and advertiser experience at Amazon. - Perform hands-on data analysis and modeling with large data sets to develop insights. - Run A/B experiments, evaluate the impact of your optimizations and communicate your results to various business stakeholders - Work closely with product managers and software engineers to design experiments and implement end-to-end solutions - Be a member of the Amazon-wide machine learning community, participating in internal and external hackathons and conferences - Help attract and recruit technical talent
US, CA, Sunnyvale
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video subscriptions such as Apple TV+, HBO Max, Peacock, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video team member, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities As an Applied Scientist at Prime Video, you will have end-to-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on. You’ll work on diverse projects that enhance Prime Video’s content localization, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include: - Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia - Innovate in advanced diffusion and flow-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test-time adaptation) to improve efficiency, controllability, and scalability. - Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre-visualization, compositing, VFX, and post-production pipelines. - Design multimodal GenAI workflows including visual-language model tooling, structured prompt orchestration, agentic pipelines. A day in the life Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world-class media creation accessible, scalable, and efficient. We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!
US, CA, Sunnyvale
As a Principal Scientist in the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically exceptional with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).