subscribe_icon.png Newsletter
Social

Build on Trainium: Responsible AI call for proposals - Fall 2025

Building the future of AI with AWS Trainium.

Share

About this CFP

What is Build on Trainium?
Build on Trainium is a $110MM credit program focused on AI research and university education to support the next generation of innovation and development on AWS Trainium. AWS Trainium chips are purpose-built for high-performance deep learning (DL) training of generative AI models, including large language models (LLMs) and latent diffusion models. Build on Trainium provides compute credits to novel AI research on Trainium, investing in leading academic teams to build innovations in critical areas including new model architectures, ML libraries, optimizations, large-scale distributed systems, and more. This multi-year initiative lays the foundation for the future of AI by inspiring the academic community to utilize, invest in, and contribute to the open-source community around Trainium. Combining these benefits with Neuron software development kit (SDK) and recent launch of the Neuron Kernel Interface (NKI), AI researchers can innovate at scale in the cloud. The program can also support model inference on AWS Trainium chips and the closely-related AWS Inferentia chips.

What are AWS Trainium and Neuron?
AWS Trainium is a purpose-built AI chip developed by AWS for accelerating building and deploying machine learning models. Built on a specialized architecture designed for deep learning, Trainium accelerates the training and inference of complex models with high output and scalability, making it ideal for academic researchers looking to optimize performance and costs. This architecture also emphasizes sustainability through resource-efficient design, reducing environmental impact. Amazon has established a dedicated Trainium research cluster featuring up to 40,000 Trainium chips, accessible via Amazon EC2 Trn instances. These instances are connected through a non-blocking, petabit-scale network using Amazon EC2 UltraClusters, enabling seamless high-performance ML training. Trn instances is optimized to deliver substantial compute power for cutting-edge AI research and development. This unique offering not only enhances the efficiency and affordability of model training but also presents academic researchers with opportunities to publish new papers on underrepresented compute architectures, thus advancing the field.

Focus on Responsible AI (RAI)
The focus of this CFP is on Responsible AI (RAI) - a major field of AI research that is critically needed for greater adoption of AI technology. Broadly speaking, AWS defines RAI to include the dimensions of 1/ Fairness, 2/ Explainability, 3/ Privacy and Security, 4/ Safety, 5/ Controllability, 6/ Veracity and robustness, 7/ Governance, and 8/ Transparency. Within RAI the five topics below are priority topics for research, based on their expected benefits to builders, customers and the scientific community.

Please develop your grant proposal addressing one or more of these topics, or make a strong case for another topic within RAI.

  1. AI safety and alignment. It is critical to ensure that artificial intelligence systems remain beneficial, controllable, and aligned with human values as AI becomes increasingly capable and autonomous. We seek proposals that utilize Trainium to advance:
    1. Robustness and Reliability: ensuring AI systems perform consistently and safely under all conditions, including adversarial attacks, distribution shifts, and edge cases
    2. Alignment and Value Learning: ensuring AI systems understand and act in accordance with human values and intentions, including inverse reinforcement learning, reward modeling, superalignment and preference learning
    3. Scalable oversight: maintaining meaningful human control over AI systems as they become more capable to include reasoning, tool usage and distributed across agents.
    4. Fairness, privacy protection and bias mitigation: Training foundation models and multi-agent AI systems with inbuilt fairness objectives, bias mitigation and protection of privacy
  2. Multi-lingual language models. Humans worldwide speak thousands of languages, but only a small fraction of these languages are used to natively train LLMs. There is a growing demand for advanced AI solutions for every human language. We seek work that:
    1. Introduces novel deep learning architectures, techniques, data and software that advance multi-lingual LLMs
    2. Trains models that excel in rarer human languages and releases datasets and tools, such as data preparation and tokenization tools for non-Latin alphabets
    3. Trains multilingual small language models (SLMs) for applications like guardrails for Asian languages
    4. Develops standardized benchmarks in knowledge, reasoning and other competencies in non-English languages with a focus on fairness and cultural inclusion
  3. Representation engineering (RE). RE is focused on understanding, analyzing, and manipulating the internal representations learned by artificial neural networks. This field investigates how models encode, transform, and utilize information to make decisions. We seek proposals that utilize Trainium for RE, including:
    1. Analysis and Visualization: techniques for understanding how neural networks encode information, including feature visualization, attribution methods, and dimensionality reduction approaches
    2. Transparency and Interpretability: methods for explanation generation, decision verification, and model inspection
    3. Modification and Control: steering how models learn representations, including architecture design, training objectives, and direct manipulation of learned representations and unlearning
    4. Security and Counter-Hallucination: detection and prevention of adversarial attack or hallucinations using RE, including through data path injections.
  4. Sustainability, Efficiency and Small Language Models (SLMs). The rapid advancement of generative AI technologies has raised resource consumption and environmental impact to a top concern of decision makers and application developers. Meanwhile, advances in SLMs enable more efficient and performant LLMs. Using cost and resource allocation as a proxy for carbon emissions offers benefits both to reduce carbon and to increase access to AI. We seek proposals that advance:
    1. Training and inference efficiency: improving the efficiency of training and inference using novel architectures, training curriculum and schedule optimization, LLM Ops and other techniques
    2. Novel SLMs: novel architectures, datasets and training strategies that advance the state of the art in SLMs such as pruning, matrix factorization, quantization, neural architecture search, and other strategies.
    3. Resource consumption of existing GenAI solutions: utilizing tools such as the Neuron SDK and Neuron Kernel Interface, research novel approaches to reduce computational overhead. Develop new algorithms, refine model architectures, and create software optimizations that significantly improve efficiency without compromising AI capabilities
    4. Real-time monitoring and optimization techniques for GenAI resource consumption: design intelligent systems capable of dynamically adjusting resource allocation based on workload demands and resource constraints. Predictive models for resource usage, adaptive algorithms for power management, and innovative approaches to balance performance and efficiency in live GenAI environments
  5. Deep learning models for synthetic data generation. VAEs, GANs and other techniques can generate fully-synthetic data such as text, images and even entire databases. These datasets can accelerate application development while protecting privacy and is indispensable for high-risk and regulated industries. The related techniques of data augmentation can accelerate the training of neural models. We seek proposals that utilize Trainium for:
    1. Foundational research: conceptual breakthroughs in realism, efficiency, scale and user control over model developer for synthetic data generation
    2. Hierarchical, multimodal and structured data: novel techniques for using models to generate fully-synthetic hierarchical and logically-constrained data as found in relational databases or multimodal and time-dependent data
    3. Advanced data augmentation: novel data augmentation methods and models for single- and multi-modal data

Timeline

Submission period: October 1 — November 5, 2025 (11:59PM Pacific Time)
Decision letters will be sent out in February 2026

Award details

Principal Investigators (PIs) may receive the following:

  • Applicants are encouraged to request AWS Promotional Credits in one of two ranges:
    • AWS Promotional Credits, up to $50,000
    • AWS Promotional Credits, up to $250,000 and beyond
  • AWS Trainium training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Awards are structured as one-time unrestricted gifts. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel.

Your receipt and use of AWS Promotional Credits is governed by the AWS Promotional Credit Terms and Conditions, which may be updated by AWS from time to time.

Eligibility requirements

Please refer to the ARA program rules on the rules and eligibility page.

Proposal requirements

PIs are encouraged to exemplify how their proposed techniques or research studies advance kernel optimization, LLM innovation, distributed systems, or developer efficiency. PIs should either include plans for open source contributions or state that they do not plan to make any open source contributions (data or code) under the proposed effort. Proposals for this CFP should be prepared according to the proposal template and are encouraged to be a maximum of 3 pages, not including Appendices.

Selection criteria

Proposals will be evaluated on the following:

  • Creativity and quality of the scientific content
  • Potential impact to the research community and society at large
  • Interest expressed in open-sourcing model artifacts, datasets, and development frameworks
  • Intention to use and explore novel hardware for AI/ML, primarily Trainium and Inferentia.

Expectations of Recipients

To the extent deemed reasonable, award recipients may acknowledge the support from ARA (“(e.g., “Research reported in this [publication/press release] was supported by an Amazon Research Award, [Cycle /Year].”). Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.

How to apply
When you're ready to submit your proposal, use the button below and follow the instructions on the site.
Submit your proposal

Related content

Work with us

See more jobs See more jobs
Senior Data Scientist, Model Customization, Generative AI Innovation Center, Model Customization
GB, London
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Data Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities As a Data Scientist, you will • Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges • Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production • Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder • Provide customer and market feedback to product and engineering teams to help define product direction About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Applied Scientist III, Alexa AI
IN, KA, Bengaluru
The Amazon Alexa AI team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI. The Applied Scientist will be in a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in Natural Language Processing (NLP) or Computer Vision (CV) related tasks. They will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. They will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon. Their work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. Key job responsibilities - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve solutions powering customer experience on Alexa+. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership.
Principal Applied Scientist, AGI Foundations
US, CA, Sunnyvale
As a Principal Scientist within 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 fearless and 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).
Senior Applied Scientist, Model Customization, Generative AI Innovation Center, Model Customization
GB, London
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. Starting in 2024, the Innovation Center launched a new Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop and optimize models to power their solutions, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Applied Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities As an Applied Scientist, you will • Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges • Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production • Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization • Provide customer and market feedback to product and engineering teams to help define product direction About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Applied Scientist, Special Projects
US, WA, Seattle
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 next-level. 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. Key job responsibilities * Partner with laboratory science teams on design and analysis of experiments * Originate and lead the development of new data collection workflows with cross-functional partners * Develop and deploy scalable bioinformatics analysis and QC workflows * Evaluate and incorporate novel bioinformatic approaches to solve critical business problems About the team 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.
Data Scientist I, SAMBA
US, NJ, Newark
At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE We are currently looking for Data Scientists to help drive innovation in understanding the incremental impact and value of product features and marketing strategies. You will be expected to work closely with our team members to implement test designs and evaluations of new product launches, promotions, and a mix of media campaigns to understand the business impact across all sales channels. At Audible, you will have an opportunity to make the best of your skillsets to both develop advanced scientific solutions and drive critical customer and business impacts. You will play a key role to drive end-to-end solutions from understanding our business and business requirements, identifying opportunities from a large amount of historical data and engaging in cutting-edge research to solve the business problems. You’ll seek to create value for both stakeholders and customers and inform findings in a clear, actionable way to managers and senior leaders. You will be at the heart of an agile and growing area at Audible. ABOUT THE TEAM Audible Data Scientists are members of a global interdisciplinary insights and research team with an integral role in the design and integration of models to automate decision making throughout the business in every country. We empower the cutting-edge machine learning and deep learning techniques in the many areas of the business. We translate business goals into agile, insightful analytics and seek to create value for both stakeholders and customers and convey findings in a clear, actionable way to managers and senior leaders. As a Data Scientist, you will... - Analyze customer data for segmentation, clustering, acquisition, retention, engagement, and recommendations - Perform content evaluation, apply natural language processing, analyze attributes and representations (in text, audio, cover art), generate content recommendations, and identify trends - Conduct product-related analyses including user click stream analysis, search engine optimization, and product recommendations - Evaluate marketing performance across earned, paid, and owned media evaluation ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
Principal Applied Scientist, AGI
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Principal Applied Scientist with a strong deep learning background, to lead the development of industry-leading technology with multimodal systems. As a Principal Applied Scientist, 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. 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 strong and 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).
Data Scientist II, People eXperience & Technology Central Science (PXTCS)
US, NY, New York
Are you passionate about conducting research to develop and grow leaders? Would you like to impact more than 1M Amazonians globally and improve the employee experience? If so, you should consider joining the People eXperience & Technology Central Science (PXTCS) team. Our goal is to be best and most diverse workforce in the world. PXTCS uses science, research, and technology to optimize employee experience and performance across the full employee lifecycle, from first contact through exit. We use economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. This individual should be skilled in core data science tools and methods, icnluding SQL, a statistical software package (e.g., R, Python, or Stata), inferential statistics, and proficient in machine learning. This person should also have strong business acumen to navigate complex, ambiguous business challenges — they should be adept at asking the right questions, knowing what methodologies to use (and why), efficiently analyzing massive datasets, and communicating results to multiple audiences (e.g., technical peers, functional teams, business leaders). In order to move quickly, deliver high-quality results, and adapt to ever-evolving business priorities, effective communication skills in research fundamentals (e.g., research design, measurement, statistics) will also be a must. Major responsibilities will include: - Managing the full life cycle of large-scale research initiatives across multiple business segments that impact leaders in our organization (i.e., develop strategy, gather requirements, manage, and execute) - Serving as a subject matter expert on a wide variety of topics related to research design, measurement, analysis - Working with internal partners and external stakeholders to evaluate research initiatives that provide bottom-line ROI and incremental improvements over time - Collaborating with a cross-functional team that has expertise in social science, machine learning, econometrics, psychometrics, natural language processing, forecasting, optimization, business intelligence, analytics, and policy evaluation - Ability to query and clean complex datasets from multiple sources, to funnel into advanced statistical analysis - Writing high-quality, evidence-based documents that help provide insights to business leaders and gain buy-in - Sharing knowledge, advocating for innovative solutions, and mentoring others Inclusive Team Culture Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have 12 affinity groups (employee resource groups) with more than 1M employees across hundreds of chapters around the world. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which reminds team members to seek diverse perspectives, learn and be curious, and earn trust. Flexibility It isn’t about which hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We offer flexibility and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth We care about your career growth, too. Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it. About the team We are a collegial and multidisciplinary team of researchers in People eXperience and Technology (PXT) that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. We leverage data and rigorous analysis to help Amazon attract, retain, and develop one of the world’s largest and most talented workforces.
Senior Data Scientist, Artificial General Intelligence, AGI
US, WA, Bellevue
The Mission of Amazon's Artificial General Intelligence (AGI) team is to "Build world-class general-purpose intelligence services that benefits every Amazon business and humanity." Are you a data enthusiast? Are you a creative big thinker who is passionate about using data to direct decision making and solve complex and large-scale challenges? If so, then this position is for you! We are looking for a motivated individual with strong analytical and communication skills to join us. In this role, you will apply advanced analytics techniques, AI/ML, and statistical concepts to derive insights from massive datasets. The ideal candidate should have expertise in AI/ML, statistical analysis, and the ability to write code for building models and pipelines to automate data and analytics processing. They will help us design experiments, build models, and develop appropriate metrics to deeply understand the strengths and weaknesses of our systems. They will build dashboards to automate data collection and reporting of relevant data streams, providing leadership and stakeholders with transparency into our system's performance. They will turn their findings into actions by writing detailed reports and providing recommendations on where we should focus our efforts to have the largest customer impact. A successful candidate should be a self-starter, comfortable with ambiguity with strong attention to detail, and have the ability to work in a fast-paced and ever-changing environment. They will also help coach/mentor junior scientists in the team. The ideal candidate should possess excellent verbal and written communication skills, capable of effectively communicating results and insights to both technical and non-technical audiences
Applied Scientist, Artificial General Intelligence
US, WA, Bellevue
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist to work on methodologies for Generative Artificial Intelligence (GenAI) models. As an Applied Scientist, you will be responsible for supporting the development of novel algorithms and modeling techniques to advance the state of the art. Your work will directly impact our customers and will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development with multi-modal Large Language Models (LLMs) and GenAI. You will have significant influence on our overall strategy by working at the intersection of engineering and applied science to scale pre-training and post-training workflows and build efficient models. You will support the system architecture and the best practices that enable a quality infrastructure. Key job responsibilities Join us to work as an integral part of a team that has experience with GenAI models in this space. We work on these areas: - Pre-training and post-training multimodal LLMs - Scale training, optimization methods, and learning objectives - Utilize, build, and extend upon industry-leading frameworks - Work with other team members to investigate design approaches, prototype new technology, scientific techniques and evaluate technical feasibility - Deliver results independently in a self-organizing Agile environment while constantly embracing and adapting new scientific advances About the team The AGI team has a mission to push the envelope in GenAI with Large Language Models (LLMs) and multimodal systems, in order to provide the best-possible experience for our customers.
See more jobs
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our monthly newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2025 Amazon.com, Inc. or its affiliates

Social