Careers

Are you excited about developing cutting-edge generative AI, large language models (LLMs), and foundation models? Are you looking for opportunities to build and deploy them on real-world problems at a truly vast scale with global impact? At AFT (Amazon Fulfillment Technologies) AI, a group of around 50 scientists and engineers, we are on a mission to build a new generation of dynamic end-to-end prediction models (and agents) for our warehouses based on GenAI and LLMs. These models will be able to understand and make use of petabytes of human-centered as well as process information, and learn to perceive and act to further improve our world-class customer experience – at Amazon scale. We are looking for a Sr. Applied Scientist who will become of the research leads in a team that builds next-level end-to-end process predictions and shift simulations for all systems in a full warehouse with the help of generative AI, graph neural networks, and LLMs. Together, we will be pushing beyond the state of the art in simulation and optimization of one of the most complex systems in the world: Amazon's Fulfillment Network. Key job responsibilities In this role, you will dive deep into our fulfillment network, understand complex processes, and channel your insights to build large-scale machine learning models (LLMs and Transformer-based GNNs) that will be able to understand (and, eventually, optimize) the state and future of our buildings, network, and orders. You will face a high level of research ambiguity and problems that require creative, ambitious, and inventive solutions. You will work with and in a team of applied scientists to solve cutting-edge problems going beyond the published state of the art that will drive transformative change on a truly global scale. You will identify promising research directions, define parts of our research agenda and be a mentor to members of our team and beyond. You will influence the broader Amazon science community and communicate with technical, scientific and business leaders. If you thrive in a dynamic environment and are passionate about pushing the boundaries of generative AI, LLMs, and optimization systems, we want to hear from you. A day in the life Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT AI team has deep expertise developing cutting edge AI solutions at scale and successfully applying them to business problems in the Amazon Fulfillment Network. These solutions typically utilize machine learning and computer vision techniques, applied to text, sequences of events, images or video from existing or new hardware. We influence each stage of innovation from inception to deployment, developing a research plan, creating and testing prototype solutions, and shepherding the production versions to launch.

The Learning & Development Science team in Amazon Logistics (AMZL) builds state-of-the-art Artificial Intelligence (AI) solutions for enhancing leadership and associate development within the organization. We develop technology and mechanisms to map the learner journeys, answer real-time questions through chat assistants, and drive the right interventions at the right time. As an Applied Scientist on the team, you will play a critical role in driving the design, research, and development of these science initiatives. The ideal candidate will lead the research on learning and development trends, and develop impactful learning journey roadmap that align with organizational goals and priorities. By parsing the information of different learning courses, they will utilize the latest advances in Gen AI technology to address the personalized questions in real-time from the leadership and associates through chat assistants. Post the learning interventions, the candidate will apply causal inference or A/B experimentation frameworks to assess the associated impact of these learning programs on associate performance. As a part of this role, this candidate will collaborate with a large team of experts in the field and move the state of learning experience research forward. They should have the ability to communicate the science insights effectively to both technical and non-technical audiences. Key job responsibilities * Apply science models to extract actionable information from learning feedback * Leverage GenAI/Large Language Model (LLM) technology for scaling and automating learning experience workflows * Design and implement metrics to evaluate the effectiveness of AI models * Present deep dives and analysis to both technical and non-technical stakeholders, ensuring clarity and understanding and influencing business partners * Perform statistical analysis and statistical tests including hypothesis testing and A/B testing * Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation

Amazon.com’s Buyer Risk Prevention's (BRP) mission is to make Amazon the safest and most trusted place worldwide to transact online. BRP safeguards every financial transaction across all Amazon sites. As such, BRP designs and builds the software systems, risk models, and operational processes that minimize risk and maximize trust in Amazon.com. The BRP organization is looking for an Applied Scientist for the Buyer Abuse team, whose mission is to combine advanced analytics with investigator insight to create mechanisms to proactively and reactively reduce the impact of abuse across Amazon. Key job responsibilities As an Applied Scientist, you will be responsible for modeling complex problems, discovering insights, and building cutting edge risk algorithms that identify opportunities through statistical models, machine learning, and visualization techniques to improve operational efficiency and reduce monetary losses and improve customer trust. You will need to collaborate effectively with business and product leaders within BRP 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 ML 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: - Invent, implement, and deploy state of the art machine learning algorithms and systems - Build prototypes and explore conceptually new solutions - Define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams - Take ownership of how ML solutions impact Amazon resources and Customer experience - 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. - Research and implement novel machine learning and statistical approaches - Maintain technical document and communicate results to diverse audiences with effective writing, visualizations, and presentations Please visit https://www.amazon.science for more information

Amazon is the 4th most popular site in the US. Our product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on a new AI-first initiative to re-architect and reinvent the way we do search through the use of extremely large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced Machine Learning (ML) on very large scale datasets, specifically through the use of aggressive systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge ML solutions and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include: - Can combining supervised multi-task training with unsupervised training help us to improve model accuracy? - Can we transfer our knowledge of the customer to every language and every locale ? - Can we build foundational ML models that can serve different business lines. This is a unique opportunity to get in on the ground floor, shape, and build the next-generation of Amazon ML. We are looking for exceptional scientists and ML engineers who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization. Key job responsibilities Train large deep learning models with hundreds of billions parameters. Build foundational ML models that can be applied to different business applications in Amazon such as Search and Ads. Set science directions for the team, in areas such as efficient model architecture, training and data optimization/scaling, model/data/pipeline parallel techniques, and much more.

Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. We are looking for an applied scientist who will work on the latest research and machine learning to build scalable personalisation solutions. You will be responsible for developing and disseminating customer-facing personalised recommendation models. This is a hands-on role working with a multidisciplinary group of engineers and scientists in the London office, focused on improving the customer experience for Prime Video and the wider Amazon organization. You will lead the design of machine learning models that scale to large quantities of data and serve low-latency recommendations to all customers worldwide. You will embody scientific rigor in designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science and engineering team that embodies the customer obsession principle by developing recommendation systems and raise the profile of Amazon as a global leader in machine learning and personalisation. Successful candidates will have strong technical ability, a focus on customers by applying a customer-first approach, and excellent teamwork and communication skills. The position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. Key job responsibilities - Research, design, and implement recommendation systems that personalise across different customer experience touch points. - Collaborate with engineers to deploy and integrate successful model experiment results into large-scale, complex Amazon production systems with low latency. - Provide machine learning thought leadership to both technical and business leaders, with the ability to think strategically about business, product, and technical challenges. - Define the science roadmap and research agenda that aligns with the organisation's priorities and production constraints. - Work with technical product managers to work backwards from what's important to customers and deliver machine-backed solutions. - Report and share results with the team and wider scientific community by authoring documents that are both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment. A day in the life You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and leaders in the Offer Tech organisation. You will be innovating and experimenting in a complex technical and business space - dealing with Amazon scale, different types of video assets (Movies, TV Shows, Live Sports, Short Videos) and balancing various business offerings (Prime, Third party channels), positively impacting millions of customers worldwide using your knowledge research, experience in building ML models to positively impact customers. About the team As a member of the Offer Recommendations team, you will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At then of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide.

Amazon is the 4th most popular site in the US. Our product search engine is one of the most heavily used services in the world, indexes billions of products, and serves hundreds of millions of customers world-wide. We are working on a new AI-first initiative to re-architect and reinvent the way we do search through the use of extremely large scale next-generation deep learning techniques. Our goal is to make step function improvements in the use of advanced Machine Learning (ML) on very large scale datasets, specifically through the use of aggressive systems engineering and hardware accelerators. This is a rare opportunity to develop cutting edge ML solutions and apply them to a problem of this magnitude. Some exciting questions that we expect to answer over the next few years include: - Can combining supervised multi-task training with unsupervised training help us to improve model accuracy? - Can we transfer our knowledge of the customer to every language and every locale ? - Can we build foundational ML models that can serve different business lines. This is a unique opportunity to get in on the ground floor, shape, and build the next-generation of Amazon ML. We are looking for exceptional scientists and ML engineers who are passionate about innovation and impact, and want to work in a team with a startup culture within a larger organization. Key job responsibilities Train large deep learning models with hundreds of billions parameters. Build foundational ML models that can be applied to different business applications in Amazon such as Search and Ads. Set science directions for the team, in areas such as efficient model architecture, training and data optimization/scaling, model/data/pipeline parallel techniques, and much more.

We’re pioneering the development of a cutting-edge Seller Foundation Model designed to capture seller interactions, predict future behaviors, and simulate responses across varied conditions. Our goal is to enhance support for our diverse seller community and foster improved outcomes for both sellers and the broader Amazon ecosystem. We are looking for passionate innovators who are excited about technology, driven by customer experience, and eager to make a lasting impact on the industry. In this role, you'll collaborate with top-tier scientists, engineers, and technical program managers (TPMs) to drive innovation and deliver exceptional results for our customers. You will lead the effort to leverage Amazon's large-scale computing resources to accelerate advances in machine learning and foundation models. If you’re enthusiastic about joining a dynamic and motivated team, this is your chance to be part of an exciting journey. Apply now and help us shape the future of seller support at Amazon!

Do you want to be part of a team that's revolutionizing Amazon's fulfillment and packaging technology? Can you commit to optimizing systems that process tens-of-millions of customer packages daily with the lowest cost to serve and a defect-free customer experience? Do you have a passion for solving complex science challenges and building a sustainable e-commerce experience? Your statistical and machine learning skills can help make that a reality on the Mechatronics and Sustainable Packaging team. We are seeking a Principal Applied Scientist who will join a team of experts in the field of Statistics, Operational Research, Machine Learning (ML), Computer Vision and Generative AI to work together to break new ground in the world of automated packaging solutions. You'll work in a collaborative environment where you can pursue ambitious research with many peta-bytes of data, work on problems that haven’t been solved before, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers, and publish your research. You'll see the work you do directly improve the packaging experience of Amazon customers in the fulfillment technology space. If you are interested in robotics, computer vision, machine learning, statistics, big data, and building scalable solutions, this role is for you. The successful candidate will have a PhD in Computer Science, Statistics, or Engineering with a strong focus on data analysis, machine learning, generative AI or a related field, and 10+ years of practical experience solving complex problems in computer vision, anomaly detection, robotics. or multi-modal classification systems. Manufacturing, packaging and/or logistic experience is a plus, but not a requirement Key job responsibilities - Advance exploratory research projects in machine learning, statistics and related fields to create defect-free packaging customer experiences - Analyze large amounts of Amazon shipments to discover patterns, find opportunities, and develop highly innovative, scalable algorithms to seize these opportunities - Validate new or improved models via statistically relevant experiments across millions of customers - Work closely with software engineering teams to build scalable prototypes for testing, and integrate successful models and algorithms in production systems at very large scale

Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like the Kindle family of products, Fire Tablets, Fire TV, Health Wellness, Amazon Echo & Astro products. This is an exciting opportunity to join Amazon in developing its next generation SOC’s for the machine learning enabled consumer products. We are looking for exceptional engineers to join the SOC development team and help develop the next generation of chips based on a revolutionary architecture. Work hard. Have Fun. Make History. Key job responsibilities What will you do? - Analyze deep learning workloads and map them to Amazon’s Neural Edge Engine - Propose and implement new hardware architectures or improvements to our existing ones, that enable future ML workloads to run efficiently on our accelerator - Collaborate closely with compiler engineers, model developers, hardware architects and product teams to build the best ML centric hardware and software solutions for our devices - Deliver hardware architecture, microarchitecture and other design collateral for our next generation ML accelerators - Build tools for modeling and performance evaluation to enable power, performance, cost options and trade-offs - Work with full stack silicon designers to realize the architecture on silicon

As a Senior Scientist at AWS AI/ML leading the Personalization and Privacy AI teams, you will have deep subject matter expertise in the areas of recommender systems, personalization, generative AI and privacy. You will provide thought leadership on and lead strategic efforts in the personalization of models to be used by customer applications across a wide range of customer use cases. Particular new directions regarding personalizing the output of LLM and their applications will be at the forefront. You will work with product, science and engineering teams to deliver short- and long-term personalization solutions that scale to large number of builders developing Generative AI applications on AWS. You will lead and work with multiple teams of scientists and engineers to translate business and functional requirements into concrete deliverables. Key job responsibilities You will be a hands on contributor to science at Amazon. You will help raise the scientific bar by mentoring, educating, and publishing in your field. You will help build the scientific roadmap for personalization, privacy and customization for generative AI. You will be a technical leader in your domain. You will be a strong mentor and lead for your team. About the team The DS3 org encompasses scientists who work closely with different AWS AI/ML product services, innovating on the behalf of our customers customers. About AWS 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. 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. This team is part of AWS Utility Computing: Utility Computing (UC) AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services.