Social

Foundation Model Development call for proposals — Winter 2024

Advancing the frontiers of foundation model development.

3 min read
Share

About this CFP

AWS offers a broad and deep set of services for organizations to create meaningful machine learning solutions faster. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every scientist and developer.

AWS is soliciting funding proposals related to foundation model (FM) development, including enhancements for dialogue, factual questioning and answering, text generation, document summarization, image generation, and more. Proposals should be expanding the state of the art in terms of training methods, with a focus on one of the following areas: 1) to reduce incorrect or nonsensical answers, 2) to reduce the sensitivity to tweaks to the input prompt, 3) ask clarifying questions when facing ambiguous questions, 4) develop efficiency enhancements across the training and hosting FM lifecycle.

We are inviting work that both critiques and enhances the state-of-the-art in FM, including but not limited to the following topics:

  • Reinforcement learning with human feedback
  • Scaling laws and their inverse, including for model fine-tuning
  • Novel datasets and training methods
  • Distillation with enhanced reasoning
  • Foundation models in novel modalities and domains, such as biology, manufacturing, fashion, etc.
  • Bias detection and mitigation throughout the foundation model lifecycle

AWS aims to advance foundation model development by funding the creation of open-source artifacts, datasets and code that benefit the research community at large, or impactful research that uses machine learning tools. AWS will provide credits for use on EC2 instances powered by AWS Trainium chips to help researchers develop and test solutions at scale. In addition to AWS Trainium, proposed research can be conducted using AWS AI Services, AWS ML Services (Amazon SageMaker, Amazon SageMaker Ground Truth, Amazon SageMaker Neo, and Amazon Augmented AI), and Amazon Bedrock.

Timeline

  • Submission period: January 17 - March 6, 2024 (11:59PM Pacific Time)
  • Decision letters will be sent out in October 2024

Award details

Selected Principal Investigators (PIs) may receive the following:

  • $250,000 in AWS Promotional Credits, which can be used on generally available EC2 instances that are powered by AWS Trainium chips
  • AWS Trainium training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Awards are structured as one-year unrestricted gifts. The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs.

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 expand the body of knowledge on pretraining and evaluation methods. 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 5 pages, not including Appendices.

Selection criteria

Funding decisions are based on the creativity and quality of the scientific content, and potential impact to the research community and society at large. AWS may solicit feedback on proposal title and abstracts from select AWS customers, but final award decisions will be made solely by AWS. Proposals will be evaluated based on their express interest in open-sourcing their model artifacts, datasets, and development frameworks. Although usage of Trainium is not a requirement, proposals will be evaluated on their intention to use and explore novel hardware for AI/ML, such as Trainium.

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. 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 engage with AWS throughout the duration of their award year including, but not limited to, providing reports on the status of their research or updates and feedback to ARA via surveys. Award recipients will have the 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.

Related content

Work with us

See more jobs See more jobs
Senior Applied Scientist, Sponsored Products and Brands
US, WA, Seattle
The Sponsored Products and Brands (SPB) 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. This position will be part of the Conversational Ad Experiences team within the Amazon Advertising organization. Our cross-functional team focuses on designing, developing and launching innovative ad experiences delivered to shoppers in conversational contexts. We utilize leading-edge engineering and science technologies in generative AI to help shoppers discover new products and brands through intuitive, conversational, multi-turn interfaces. We also empower advertisers to reach shoppers, using their own voice to explain and demonstrate how their products meet shoppers' needs. We collaborate with various teams across multiple Amazon organizations to push the boundary of what's possible in these fields. We are seeking a science leader for our team within the Sponsored Products & Brands organization. You'll be working with talented scientists, engineers, and product managers to innovate on behalf of our customers. An ideal candidate is able to navigate through ambiguous requirements, working with various partner teams, and has experience in generative AI, large language models (LLMs), information retrieval, and ads recommendation systems. Using a combination of generative AI and online experimentation, our scientists develop insights and optimizations that enable the monetization of Amazon properties while enhancing the experience of hundreds of millions of Amazon shoppers worldwide. If you're fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey! Key job responsibilities - Serve as a tech lead for defining the science roadmap for multiple projects in the conversational ad experiences space powered by LLMs. - Build POCs, optimize and deploy models into production, run experiments, perform deep dives on experiment data to gather actionable learnings and communicate them to senior leadership - Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. - Work closely with product managers to contribute to our mission, and proactively identify opportunities where science can help improve customer experience - Research new machine learning approaches to drive continued scientific innovation - Be a member of the Amazon-wide machine learning community, participating in internal and external meetups, hackathons and conferences - Help attract and recruit technical talent, mentor scientists and engineers in the team
Senior Economist, Amazon Stores Economics and Science (SEAS)
US, CA, Palo Alto
Stores Economics and Science (SEAS) is an interdisciplinary team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science, collaborating with partner teams, and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. We are looking for a Senior Economist to drive high-impact economic analysis and modeling that shapes how Amazon's Stores business makes decisions. In this role, you will work in a team of economists, scientists, and engineers to identify key business questions, design rigorous analytical frameworks, and deliver actionable insights to senior leadership and partner teams. You will own end-to-end research (from problem formulation and data analysis through modeling and stakeholder communication) in areas such as pricing, demand estimation, substitution measurement, and experiment design. Your responsibilities include developing economic models and empirical analyses that inform strategic decisions, designing and analyzing experiments, and translating complex findings into clear recommendations for technical and non-technical audiences. You will also mentor junior economists and help raise the bar on economic rigor across partner teams. The ideal candidate has a PhD in Economics and deep expertise in causal inference and applied econometrics. Experience with large-scale data, proficiency in statistical programming (Python or similar), and familiarity with machine learning methods are a plus. To be successful in this role, you should be comfortable operating with ambiguity, able to independently scope and prioritize research agendas, skilled at influencing decisions through rigorous analysis, and comfortable with using AI tools.
Quantum Research Scientist
US, CA, Pasadena
The Amazon Web Services (AWS) Center for Quantum Computing in Pasadena, CA, is looking to hire a Quantum Research Scientist in the device measurement group. You will join a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers working at the forefront of quantum computing. You should have a deep and broad knowledge of experimental measurement techniques. Candidates with a track record of original scientific contributions will be preferred. We are looking for candidates with strong engineering principles, resourcefulness and a bias for action, superior problem solving, and excellent communication skills. Working effectively within a team environment is essential. As a research scientist you will be expected to work on new ideas and stay abreast of the field of experimental quantum computation. Key job responsibilities In this role, you will drive improvements in qubit performance by characterizing the impact of environmental and material noise on qubit dynamics. This will require designing experiments to assess the role of specific noise sources, ensuring the collection of statistically significant data through automation, analyzing the results, and preparing clear summaries for the team. Finally, you will work with hardware engineers, material scientists, and circuit designers to implement changes which mitigate the impact of the most significant noise sources.
Senior Applied Scientist, International Seller Services
IN, TS, Hyderabad
At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our mission in International Seller Services (ISS) is to provide technology solutions for improving the seller and customer experience, drive seller compliance, maximize seller success, and improve internal workforce productivity. Team's main focus is to build products that are scalable across different regions of the world, while working in partnership with ISS regional stakeholders and multiple partner teams across Amazon. As an Applied Scientist, you will be responsible for modeling complex problems, discovering insights, and building risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency. As an Applied Scientist, you will leverage your expertise in Machine Learning, Natural Language Processing (NLP), and Large Language Models (LLM) to develop innovative solutions for Amazon's ISS team. You'll be responsible for modeling complex problems, building innovative algorithms, and discovering actionable insights through statistical models and visualization techniques to enhance operational efficiency in the e-commerce space. The role combines usage of latest AI technology with practical business applications, requiring someone passionate about transforming the way we interact with technology while delivering measurable impact through advanced analytics and machine learning solutions. You will need to collaborate effectively with business and product leaders within ISS and cross-functional teams to build scalable solutions against high organizational standards. The candidate should be able to apply a breadth of tools, data sources, and Data Science techniques to answer a wide range of high-impact business questions and proactively present new insights in concise and effective manner. The candidate should be an effective communicator capable of independently driving issues to resolution and communicating insights to non-technical audiences. This is a high impact role with goals that directly impacts the bottom line of the business. Responsibilities: - Analyze terabytes of data to define and deliver on complex analytical deep dives to unlock insights and build scalable solutions through science to ensure security of Amazon’s platform and transactions Build Machine Learning and/or statistical models that evaluate the transaction legitimacy and track impact over time Ensure data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, and cross-lingual alignment/mapping Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams Develop efficient data querying infrastructure for both offline and online use cases Collaborate with cross-functional teams from multidisciplinary science, engineering and business backgrounds to enhance current automation processes Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use. Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations Key job responsibilities • You will extract huge volumes of data from various sources and construct complex analyses. • You should be detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion • You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions. You own customer relationship about data and execute tasks that are manifestations of such ownership, like ensuring high data availability, low latency, documenting data details and transformations and handling user notifications and training • You will work with distributed machine learning and statistical algorithms upon a large Hadoop cluster to harness enormous volumes at scale to serve our customers
Applied Scientist, Central Seller Fulfillment
IN, KA, Bengaluru
We are seeking a stellar Machine Learning scientist who has experience developing and shipping large scale ML products with visible customer impact. We would prefer if your previous work has been in developing scalable Agentic, RL or forecasting systems. Strong academic background in Statistics, Machine Learning & Deep Learning is required with Tier -1 publications being a plus. • Master’s degree in CS or ML related fields • Scientist/Tech Lead creating and shipping impactful ML products. • Ability to write clear, structured and modularized code in Python. • Expertise in Deep Learning frameworks such as Tensorflow, Keras and Pytorch & Agentic frameworks such as LangChain, Crew AI etc. • Industry experience designing complex scalable AI systems. • Experience and technical expertise across various science domains. Crucial ones being statistics, deep & machine learning. • Experience creating data pipelines & proficient in querying data from Spark/HIVE/Redshift/other large scale data warehousing platforms. • Expert in distilling informal customer requirements into problem definitions, dealing with ambiguity and formulating ML products to solve these problems. Key job responsibilities In this position, you will be a key contributor (with direct leadership visibility) building, productionizing (real & batch) and measuring impact of state of the art personalized Gen AI systems for Amazon global selling partners and contribute to Amazon wide research in this area in the form of publications and white papers. You will work with global leaders and teams across time zones on a regular basis. About the team Millions of Sellers list their products for sale on the Amazon Marketplace. Sellers are a critical part of Amazon’s ecosystem to deliver on our vision of offering the Earth’s largest selection and lowest prices. In this ecosystem our team plays a critical role in enabling Sellers across EU5, China, Japan, Australia, Brazil and Turkey to make their Selection available to customers globally and deliver the experience they have come to expect from Amazon. We help independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. We are pushing the boundaries of these machine learning tools in areas of Agentic, recommendation and forecasting systems to help our sellers sell more and across borders.
Applied Scientist, Central Seller Fulfillment
IN, KA, Bengaluru
We are seeking a stellar Machine Learning scientist who has experience developing and shipping large scale ML products with visible customer impact. We would prefer if your previous work has been in developing scalable Agentic, RL or forecasting systems. Strong academic background in Statistics, Machine Learning & Deep Learning is required with Tier -1 publications being a plus. • Master’s degree in CS or ML related fields • Scientist/Tech Lead creating and shipping impactful ML products. • Ability to write clear, structured and modularized code in Python. • Expertise in Deep Learning frameworks such as Tensorflow, Keras and Pytorch & Agentic frameworks such as LangChain, Crew AI etc. • Industry experience designing complex scalable AI systems. • Experience and technical expertise across various science domains. Crucial ones being statistics, deep & machine learning. • Experience creating data pipelines & proficient in querying data from Spark/HIVE/Redshift/other large scale data warehousing platforms. • Expert in distilling informal customer requirements into problem definitions, dealing with ambiguity and formulating ML products to solve these problems. Key job responsibilities In this position, you will be a key contributor (with direct leadership visibility) building, productionizing (real & batch) and measuring impact of state of the art personalized Gen AI systems for Amazon global selling partners and contribute to Amazon wide research in this area in the form of publications and white papers. You will work with global leaders and teams across time zones on a regular basis. About the team Millions of Sellers list their products for sale on the Amazon Marketplace. Sellers are a critical part of Amazon’s ecosystem to deliver on our vision of offering the Earth’s largest selection and lowest prices. In this ecosystem our team plays a critical role in enabling Sellers across EU5, China, Japan, Australia, Brazil and Turkey to make their Selection available to customers globally and deliver the experience they have come to expect from Amazon. We help independent sellers compete against our first-party business by investing in and offering them the very best selling tools we could imagine and build. We are pushing the boundaries of these machine learning tools in areas of Agentic, recommendation and forecasting systems to help our sellers sell more and across borders.
Machine Learning Scientist / Applied Scientist, EU Prime and Marketing Analytics & Science (PRIMAS)
ES, M, Madrid
Are you interested in changing how Amazon does marketing — moving beyond platform-optimized broad reach to campaigns that find the right customer, at the right moment, using Amazon's unmatched 1P data? We are seeking an Applied Scientist to join PRIMAS (Prime & Marketing Analytics and Science). In this role, you will design and run the experiments that answer the foundational question for EU marketing: does adding 1P audience signal on top of Value-Based Optimization (VBO) improve marketing efficiency — and if so, for which customer cohorts, on which surfaces, and at what scale? Amazon's current marketing model is largely platform-led: we set objectives and let platforms optimize toward conversion. This approach works well for broad acquisition but systematically underserves lifecycle goals — it cannot distinguish between a Bargain Hunter who will never pay full price and a high-potential customer one nudge away from becoming a Prime member. This role sits at the center of changing that. You will build the 1P audiences, design the experiments that test them, and generate the evidence that guides how Amazon allocates hundreds of millions in marketing spend. Year 1 is an experimentation year. You will deploy 1P audiences across multiple surfaces and channels — Meta, Google, Amazon Display Ads — and measure incrementally against VBO baselines. The goal is not to replace platform optimization but to understand when and where the combination of 1P signal + VBO outperforms VBO alone, and to build the experimental infrastructure that makes this learning scalable. Key job responsibilities 1P Audience Development & Experimentation: - Build and validate 1P audience segments from Amazon behavioral, transactional, and lifecycle data - Design experiments that isolate the incremental effect of 1P audience signal over platform VBO baselines - Deploy audiences across activation surfaces and establish measurement standards that make cross-surface comparison valid Causal Measurement & Incrementality: - Apply causal inference methods to measure the true incremental lift of audience-based targeting vs. VBO - Develop power analysis frameworks and guardrails that enable rapid experimentation without underpowered or conflated tests - Deliver optimization recommendations grounded in experimental evidence: which cohorts respond, which surfaces deliver, which creative strategies drive behavior change Scaling the Learning: - Build reusable audience and measurement frameworks that can be deployed across campaigns and channels — year 1 experiments should produce infrastructure, not one-off analyses - Document experimental learnings in a way that informs both the 2026 roadmap and the business case for investing further in 1P audience capabilities in 2027+ - Partner with engineering and PMT to translate validated audience prototypes into production-ready solutions that scale beyond the experimentation phase About the team The PRIMAS team, is part of a larger tech tech team of 100+ people called WIMSI (WW Integrated Marketing Systems and Intelligence). WIMSI core mission is to accelerate marketing technology capabilities that enable de-averaged customer experiences across the marketing funnel: awareness, consideration, and conversion.
Applied Scientist, AWS Automated Reasoning
US, MA, Boston
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. Develop strategic plans to identify fundamentally new solutions for business problems. Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & 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, training, 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
Senior Data Scientist, Sponsored Products
US, NY, New York
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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. Amazon Ads Response Prediction team is your choice, if you want to join a highly motivated, collaborative, and fun-loving team with a strong entrepreneurial spirit and bias for action. We are seeking an experienced and motivated Machine Learning Applied Scientist who loves to innovate at the intersection of customer experience, deep learning, and high-scale machine-learning systems. Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. We are looking for a talented Machine Learning Applied Scientist for our Amazon Ads Response Prediction team to grow the business. We are providing advanced real-time machine learning services to connect shoppers with right ads on all platforms and surfaces worldwide. Through the deep understanding of both shoppers and products, we help shoppers discover new products they love, be the most efficient way for advertisers to meet their customers, and helps Amazon continuously innovate on behalf of all customers. Key job responsibilities * 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 to optimize all aspects of Sponsored Products and Brands business
Senior Applied Scientist, Delivery Foundation Model
US, CA, Santa Clara
Join the next science and engineering revolution at Amazon's Delivery Foundation Model team, where you'll work alongside world-class scientists and engineers to pioneer the next frontier of logistics through advanced AI and foundation models. We are seeking an exceptional Senior Applied Scientist to help develop innovative foundation models that enable delivery of billions of packages worldwide. In this role, you'll combine highly technical work with scientific leadership, ensuring the team delivers robust solutions for dynamic real-world environments. Your team will leverage Amazon's vast data and computational resources to tackle ambitious problems across a diverse set of Amazon delivery use cases. Key job responsibilities - Design and implement novel deep learning architectures combining a multitude of modalities, including image, video, and geospatial data. - Solve computational problems to train foundation models on vast amounts of Amazon data and infer at Amazon scale, taking advantage of latest developments in hardware and deep learning libraries. - As a foundation model developer, collaborate with multiple science and engineering teams to help build adaptations that power use cases across Amazon Last Mile deliveries, improving experience and safety of a delivery driver, an Amazon customer, and improving efficiency of Amazon delivery network. - Guide technical direction for specific research initiatives, ensuring robust performance in production environments. - Mentor fellow scientists while maintaining strong individual technical contributions. A day in the life As a member of the Delivery Foundation Model team, you’ll spend your day on the following: - Develop and implement novel foundation model architectures, working hands-on with data and our extensive training and evaluation infrastructure - Guide and support fellow scientists in solving complex technical challenges, from trajectory planning to efficient multi-task learning - Guide and support fellow engineers in building scalable and reusable infra to support model training, evaluation, and inference - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems- Drive technical discussions within the team and and key stakeholders - Conduct experiments and prototype new ideas - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team The Delivery Foundation Model team combines ambitious research vision with real-world impact. Our foundation models provide generative reasoning capabilities required to meet the demands of Amazon's global Last Mile delivery network. We leverage Amazon's unparalleled computational infrastructure and extensive datasets to deploy state-of-the-art foundation models to improve the safety, quality, and efficiency of Amazon deliveries. Our work spans the full spectrum of foundation model development, from multimodal training using images, videos, and sensor data, to sophisticated modeling strategies that can handle diverse real-world scenarios. We build everything end to end, from data preparation to model training and evaluation to inference, along with all the tooling needed to understand and analyze model performance. Join us if you're excited about pushing the boundaries of what's possible in logistics, working with world-class scientists and engineers, and seeing your innovations deployed at unprecedented scale.
See more jobs

Work with us

See more jobs See more jobs
Data Scientist, network planning optimization world wide, Supply Chain Optimization Technology
GB, London
Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? We are looking for a Data Scientist who will be responsible to develop scientific solutions to optimize our fulfillment strategy across multiple regions of the world (EU, JP, IN and more), to maximize our Customer Experience and minimize our cost and carbon footprint. You will partner with the worldwide scientific community to help design the optimal fulfillment strategy for Amazon. You will also collaborate with technical teams to develop optimization tools for network flow planning and execution systems. Finally, you will also work with business and operational stakeholders to influence their strategy and gather inputs to solve problems. To be successful in the role, you will need deep analytical skills and a strong scientific background. The role also requires excellent communication skills, and an ability to influence across business functions at different levels. You will work in a fast-paced environment that requires you to be detail-oriented and comfortable in working with technical, business and technical teams. Key job responsibilities - Design and develop mathematical models to optimize inventory placement and product flows. - Design and develop statistical and optimization models for planning Supply Chain under uncertainty. - Manage several, high impact projects simultaneously. - Consult and collaborate with business and technical stakeholders across multiple teams to define new opportunities to optimize our Supply Chain. - Communicate data-driven insights and recommendations to diverse senior stakeholders through technical and/or business papers. - Leverage LLMs to improve explainability of our optimization solutions and drive engagement from supply chain planners across the world.
Sr Data Scientist, Seller Partner Trust Analytics
US, WA, Seattle
As we strive to be Earth's most customer-centric company, Amazon has reinvented how hundreds of millions of people shop online – providing customers with the opportunity to find and discover virtually anything they want to buy and providing millions of sellers with a platform for growing successful businesses. We are looking for an exceptional business analyst to help us develop new ways to build trust and loyalty with sellers, a crucial component of our flywheel Sellers’ trust in Amazon is our top priority and in this role, you will be tasked with building that trust over time by diving deep into how we measure our progress and helping to identify and prioritize key areas of focus. Amazon’s growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems. The successful candidate will be a self-starter, comfortable with ambiguity and be able to create and maintain efficient & automated processes. They will set the vision, strategy, and roadmap, and work alongside with stakeholders in the organization to make it happen. They know and love working with business intelligence tools, can model multidimensional datasets, and can partner effectively with business leaders to answer key business questions. They are analytical and creative, and don’t quit. This is a role with high visibility to senior leadership and with high opportunity for impact for those willing to roll up their sleeves and dive deep to achieve results. Key job responsibilities Use advanced statistical and machine learning techniques to extract insights from large-scale streaming, ad delivery, and auction data sets. - Design and implement end-to-end data science workflows from data acquisition and cleaning through model development, offline evaluation, A/B testing, and production deployment in partnership with product and engineering teams - Build, validate, and maintain the statistical models that support the roadmap including Supply tier classification and Supply Quality Index, ad tolerance and fatigue scoring, and propensity and disengagement prediction - Partner with product and economist teams to design hold out experiments to measure impact of Ad load on revenue and customer engagement; define north star metrics, power calculations, holdout structures, and promotion gates for every major lever. - Support scalable, self-service analytics by building curated datasets for PVa product, ops, sales, and science covering supply, yield, CX, and advertiser diversification outcomes. - Partner with product stakeholders and science peers to identify strategic, data-driven opportunities to improve the customer experience and advertiser results. - Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders - Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organizatio
Research Software Engineer, Calibration, MQS Center for Quantum Computing
US, CA, San Francisco
The Models, Quantum, and Silicon (MQS) Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer. We are looking to hire a Research Software Engineer to join our growing Software team. You will work closely with our experimental physics teams to enable their work characterizing, calibrating, and operating novel quantum devices. The ideal candidate should be able to translate high-level science requirements into software implementations (e.g. Python APIs/frameworks, data analysis pipelines, calibration nodes) that are performant, scalable, and intuitive. This requires someone who (1) has a strong desire to work within a team of scientists and engineers, and (2) demonstrates ownership in initiating and driving projects to completion. This role has a particular emphasis on working directly with experimental physicists to develop scientific software workflows that enable scaling to larger quantum devices. Inclusive Team Culture Here at Amazon, 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 conferences, inspire us to never stop embracing our uniqueness. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Export Control Requirement Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility. Key job responsibilities - Architect extensible & intuitive frameworks for running quantum computing experiments and analyzing data. - Leverage the latest techniques in quantum calibration to enable scaling to larger devices. - Optimize the performance of experiment & analysis tools to enable faster experiment throughput. - Develop dashboards that allow experimentalists to inspect and control the state of quantum device calibration. - Deploy and maintain cloud infrastructure that supports increasingly-complex science workflows. - Empower scientists to actively contribute to the codebase through mentorship and documentation. We are looking for candidates with strong engineering principles, a bias for action, superior problem-solving, and excellent communication skills. Working effectively within a team environment is essential. As a Research Software Engineer embedded in a broader research science organization, you will have the opportunity to work on new ideas and stay abreast of the field of experimental quantum computation. A day in the life The majority of your time will be spent on projects that extend the functional capabilities or performance of our internal research software stack. This requires working backwards from the needs of our science staff in the context of our larger experimental roadmap. You will translate science and software requirements into design proposals balancing implementation complexity against time-to-delivery. Once a design proposal has been reviewed and accepted, you’ll drive implementation and coordinate with internal stakeholders to ensure a smooth roll out. Because many high-level experimental goals have cross-cutting requirements, you’ll often work closely with other engineers or scientists or on the team. About the team You will be joining the Software group within the MQS Center of Quantum Computing. Our team is comprised of scientists and software engineers who are building scalable software that enables quantum computing technologies.
Sr. Applied Scientist, Prime Video - Generative AI
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!
Data Scientist II, AWS Managed Operations Intelligence (MOI) - Data Science
US, VA, Arlington
Amazon Web Services (AWS) is the world leader in providing a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world! Passionate about building, owning and operating massively scalable systems? Want to make a billion-dollar impact? If so, we have an exciting opportunity for you. The AWS Managed Operations (MO) organization was founded in April 2023, with the objective to reduce operational load and toil through long-term engineering projects. MO is building the best-in-class engineering and operations team that will own the day-to-day operations for AWS Regions; improving the availability, reliability, latency, performance and efficiency to operate AWS regions. The AWS Managed Operations Intelligence (MOI) Team is looking for a Data Scientist to lead the research and thought leadership to drive our data and insight strategy for AWS. You will be expected to serve as a Full Stack Data Scientist. You will be responsible for driving data-driven transformation across the organization. In this role, you will be responsible for the end-to-end data science lifecycle, from data exploration, ETL, model development and data visualization. You will leverage a diverse set of tools and technologies, including general analytical frameworks (Spark, Airflow, etc.), AI frameworks (Hugging Face, etc.) and various machine learning frameworks, to tackle complex business problems. Your analytics research will provide direction on the technology strategy of the Managed Operations organization. Your Decision Science artifacts will provide insights that inform AWS' Operations and Site Reliability Engineering teams. You will work on ambiguous and complex business and research science problems at scale. You are and comfortable working with cross-functional teams and systems. This role will sit in our new headquarters in Northern Virginia, where Amazon will invest $2.5 billion dollars, occupy 4 million square feet of energy efficient office space, and create at least 25,000 new full-time jobs. Our employees and the neighboring community will also benefit from the associated investments from the Commonwealth including infrastructure updates, public transportation improvements, and new access to Reagan National Airport. By working together on behalf of our customers, we are building the future one innovative product, service, and idea at a time. Are you ready to embrace the challenge? Come build the future with us. This position requires that the candidate selected be a U.S. citizen. 10012 Key job responsibilities - Work with large and complex data sets to solve a wide array of challenging problems using different analytical approaches - Develop ML/AI models. Partner with software teams to productionalize these models. - Data Pipeline and Infrastructure: design and implementation of data pipelines - Metric Development and Monitoring: Define and develop advanced, customized metrics and key performance indicators (KPIs) that capture the nuances of the organization's strategic objectives and operational complexities. Continuously monitor and evaluate the performance of metrics A day in the life Why AWS? Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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. About AWS Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. AWS Infrastructure Services (AIS) AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. Inclusive Team Culture AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do. 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. About the team The Managed Operations Intelligence (MOI) Team helps AWS operate its services across the world. We help monitor AWS operations by providing insights and recommendations on AWS operations. This position requires that the candidate selected be a U.S. citizen.
Comm Systems Engineer, Wireless Systems
US, TX, Austin
Amazon Leo is an initiative to launch a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband connectivity to unserved and underserved communities around the world. As a Systems Engineer, this role is primarily responsible for the design, development and integration of communication payload and customer terminal systems. The Role: Be part of the team defining the overall communication system and architecture of Amazon Leo’s broadband wireless network. This is a unique opportunity to innovate and define groundbreaking wireless technology at global scale. The team develops and designs the communication system for Leo and analyzes its overall system level performance such as for overall throughput, latency, system availability, packet loss etc. This role in particular will be responsible for leading the effort in designing and developing advanced technology and solutions for communication system. This role will also be responsible developing advanced physical layer + protocol stacks systems as proof of concept and reference implementation to improve the performance and reliability of the LEO network. In particular this role will be responsible for using concepts from digital signal processing, information theory, wireless communications to develop novel solutions for achieving ultra-high performance LEO network. This role will also be part of a team and develop simulation tools with particular emphasis on modeling the physical layer aspects such as advanced receiver modeling and abstraction, interference cancellation techniques, FEC abstraction models etc. This role will also play a critical role in the integration and verification of various HW and SW sub-systems as a part of system integration and link bring-up and verification. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.
Applied Scientist II, Strategic Account Services (SAS)
GB, London
Amazon Strategic Account Services (SAS) Tech Organization is looking for an Applied Scientist Applied Scientist who can autonomously drive scientific innovations from research to production, developing sophisticated AI solutions that serve both Amazon's global seller base and internal Marketplace Consultants. Working in a highly collaborative environment, you'll leverage expertise in machine learning, operations research, and statistics to translate theoretical advances in LLMs, probabilistic modeling, and optimization into practical applications. The role demands strong capabilities in prototyping and iterative improvement, bridging cutting models with real-world applications while maintaining scientific rigor and measurable business impact. Key job responsibilities - Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale - Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning - Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges - Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale - Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact - Pioneer novel applications of foundation models and generative AI, developing sophisticated evaluation frameworks while maintaining Amazon's high standards for accuracy and reliability - Lead technical discussions across organizational boundaries, effectively communicating complex scientific concepts to diverse stakeholders while staying at the forefront of ML/AI research advancements About the team What is Amazon Strategic Account Services (SAS)? The SAS team aims to accelerate the full potential of our Sellers, helping them to navigate the increasing complexity of the e-commerce space. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and a Customer-focused approach to achieve commercial goals of Amazon Sellers.
Senior Applied Scientist, Sponsored Products Bidding
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Within Sponsored Products, the Bidding team is responsible for defining and delivering a collection of advertising products around bid controls (dynamic bidding, bid recommendations, etc.) that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Key job responsibilities As a Senior Applied Scientist on this team, you will: • Lead a new initiative across Sponsored Products Bidding focused on AI/ML based features. • Be the technical leader in AI, Machine Learning; lead efforts within this team and across other teams. • Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. • Drive end-to-end AI/Machine Learning projects that have a high degree of ambiguity, scale, complexity. • Build models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your AI/ML models. • Run A/B experiments, gather data, and perform statistical analysis. • Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. • Research new and innovative AI/ machine learning approaches. • Recruit Applied Scientists to the team and provide mentorship. A day in the life Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon's Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. About the team The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through the latest generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. The SPB Bidding team within Sponsored Products and Brands is focused on guiding and supporting Millions of advertisers to meet their advertising needs of creating and managing ad campaigns. At this scale, the complexity of diverse advertiser goals, campaign types, and market dynamics creates both a massive technical challenge and a transformative opportunity: even small improvements in bidding systems can have outsized impact on advertiser success and Amazon’s retail ecosystem. Our vision is to build a highly personalized, context-aware bidding system that leverages auction simulations, ML models, and optimization algorithms. This framework, will operate across SPB bidding system and proactively delivering value based on deep understanding of the advertiser. To execute this vision, we collaborate closely with stakeholders across Ad Console, Sales, and Marketing to identify opportunities—from high-level product guidance down to granular recommendations—and deliver them through a tailored, personalized experience. Our work is grounded in state-of-the-art bidding agent architectures, tool integration, reasoning frameworks, and model customization approaches (including tuning and preference optimization), ensuring our systems are both scalable and adaptive.
Applied Scientist II, RBS Tech
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 help the team leverage your expertise, by coaching and mentoring. You will contribute to the professional development of colleagues, improving their technical knowledge and the engineering practices. You will independently as well as guide team to 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.
Applied Scientist, Structural Design Integrity, Hardware - Product Integrity
CN, 31, Shanghai
As an 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
See more jobs
Amazon Research Awards.jpg

Amazon Research Awards

Collaborating with scientists around the world to fund research, share knowledge and encourage innovation.
Learn more
View from space of a connected network around planet Earth representing the Internet of Things.
Get more from Amazon Science
Subscribe to our newsletter

Amazon.com | Conditions of Use | Privacy | © 1996-2026 Amazon.com, Inc. or its affiliates

Social