Careers

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied scientist with a strong background in responsible AI, deep learning and large language models (LLMs) techniques to develop and deploy world-class foundation models. Key job responsibilities As an Applied Scientist with the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources and collaborate with colleagues cross-AGI to achieve this objective. Your work will have a direct impact to AGI's business and customers through the foundation models we develop and depoly. About the team Our team's mission is to develop and deploy industry-leading foundation models that set the benchmark for the industry, comply with the relevant responsible RAI policies and delight our customers in the process.

We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science team to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities Develop machine learning algorithms for high-scale recommendations problems. Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. Collaborate with software engineers to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply cutting edge machine learning algorithms to solve real world problems with significant impact? The AI/ML Platforms (AMP) Team in World Wide Public Sector (WWPS) at AWS is a strategic team that helps AWS customers implement AI/ML solutions and realize transformational business opportunities. This is a team of strategists, data scientists, engineers, and solution architects working step-by-step with customers to build bespoke solutions that harness the power of AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The AMP team provides guidance on best practices for applying generative AI responsibly and cost efficiently. This position requires up to 10% travel. It is expected to work from one of the above locations (or customer sites) at least 1+ days in a week. This is not a remote position. You are expected to be in the office or with customers as needed. This position requires that the candidate selected be a US Citizen and obtain and maintain an active TS/SCI security clearance. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities Key job responsibilities As an Data Scientist, you will: Collaborate with AI/ML scientists and architects to Research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder Provide customer and market feedback to Product and Engineering teams to help define product direction A day in the life You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Data Scientists capable of using data engineering, data architecture and machine learning techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. About the team 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. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. 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. 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 in the cloud. 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.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied scientist with a strong background in responsible AI, deep learning and large language models (LLMs) techniques to develop and deploy world-class foundation models. Key job responsibilities As an Applied Scientist with the AGI team, you will work with world-class scientists and engineers to develop novel data, modeling and engineering solutions to support the responsible AI initiatives at AGI. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources and collaborate with colleagues cross-AGI to achieve this objective. Your work will have a direct impact to AGI's business and customers through the foundation models we develop and depoly. About the team Our team's mission is to develop and deploy industry-leading foundation models that set the benchmark for the industry, comply with the relevant responsible RAI policies and delight our customers in the process.

Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses. If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom-line, we want to talk to you. Major responsibilities 3+ years of building machine learning models for business application experience PhD, or Master's degree and 2+ years of applied research experience Knowledge of programming languages such as C/C++, Python, Java or Perl Experience programming in Java, C++, Python or related language You have expertise in one of the applied science disciplines, such as machine learning, natural language processing, computer vision, Deep learning You are able to use reasonable assumptions, data, and customer requirements to solve problems. You initiate the design, development, execution, and implementation of smaller components with input and guidance from team members. You work with SDEs to deliver solutions into production to benefit customers or an area of the business. You assume responsibility for the code in your components. You write secure, stable, testable, maintainable code with minimal defects. You understand basic data structures, algorithms, model evaluation techniques, performance, and optimality tradeoffs. You follow engineering and scientific method best practices. You get your designs, models, and code reviewed. You test your code and models thoroughly You participate in team design, scoping and prioritization discussions. You are able to map a business goal to a scientific problem and map business metrics to technical metrics. You invent, refine and develop y

Amazon Web Services (“AWS”) is looking for an outstanding Senior Data Scientist to join the AWS International Product Management and Expansion Strategy team. This is your opportunity to be a core part of the AWS team that has a direct impact on global strategic planning and decision-making. Today, AWS serves customers globally from over 190 countries through multiple infrastructure Regions. From these Regions, AWS offers over 200 fully featured cloud services which redefine business agility, reduce the cost of IT infrastructure, and elevate the role of IT as an enabler of business organizations. As a Senior Data Scientist on this team, you will get an exciting opportunity to structure and solve challenging business problems that help develop long-term growth strategies for AWS’s international business. We are looking for a seasoned professional with strong experience with operations research and/or AI/machine learning especially those with experience in seeking deep insights around customer adoption patterns globally. In this role, you will study patterns and structure models to quickly approach ambiguous problems with mathematical models that drive the adoption of AWS long-term to meaningfully impact AWS’s growth. To support their proposals, candidates should be able to mine large data sets independently, analyze patterns with any necessary programming and statistical techniques in a fast-paced environment. You will work closely with the business and technical teams to analyze many non-standard and unique business problems, and innovate with creative-problem solving to deliver actionable output to stakeholders. A successful candidate will be a self-starter, comfortable with ambiguity, with a working knowledge of cloud technology, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment, a penchant to explain findings backed by sound statistical techniques, synthesize the business impact of findings, and have an ability to collaborate as well as effectively influence cross-functional teams. Come help us make history! Key job responsibilities The key strategic objectives of this role include, but are not limited to: • Lead logical thinking to quickly turn high level ambiguous business problems into mathematical models • Help identify causal elements behind business trends to drive solution approaches that will let AWS expand faster internationally • Provide thought leadership to identify new correlations between emerging technology trends and global customer adoption to establish intuitive, but authoritative models that forecast or estimate impact to the business • Answer complex business questions around downstream impact and customer adoption patterns with statistical techniques/business rigor • Work with regional strategy managers to distill business trends unique to geographies • Develop Excel/Python/AWS AI/ML tool-based models to provide user friendly insights for business stakeholders and provide short- or long-term business projections that reflect cloud computing adoption About the team 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.

Do you enjoy solving challenging problems and driving innovations in research? Are you seeking for an environment with a group of motivated and talented scientists like yourself? Do you want to create scalable optimization models and apply machine learning techniques to guide real-world decisions? Do you want to play a key role in the future of Amazon transportation and operations? Come and join us at Amazon's Modeling and Optimization team (MOP). Key job responsibilities An Applied Scientist in the Modeling and Optimization (MOP) team - provides analytical decision support to Amazon planning teams via applying advanced mathematical and statistical techniques. - collaborates effectively with Amazon internal business customers, and is their trusted partner - is proactive and autonomous in discovering and resolving business pain-points within a given scope - is able to identify a suitable level of sophistication in resolving the different business needs - is confident in leveraging existing solutions to new problems where appropriate and is independent in designing and implementing new solutions where needed - is aware of the limitations of their proposed solutions and is proactive in communicating them to the business, and advances the application of sciences towards Amazon business problems by bringing new methods, ideas, and practices to the team and scientific community. A day in the life - Your will be developing model-based optimization, simulation, and/or predictive tools to identify and evaluate opportunities to improve customer experience, network speed, cost, and efficiency of capital investment. - You will quantify the improvements resulting from the application of these tools and you will evaluate the trade-offs between potentially competing objectives. - You will develop good communication skills and ability to speak at a level appropriate for the audience, will collaborate effectively with fellow scientists, software development engineers, and product managers, and will deliver business value in a close partnership with many stakeholders from operations, finance, IT, and business leadership. About the team - At the Modeling and Optimization (MOP) team, we use mathematical optimization, algorithm design, statistics, and machine learning to improve decision-making capabilities across WW Operations and Amazon Logistics. - We focus on transportation topology, labor and resource planning for fulfillment facilities, routing science, visualization research, data science and development, and process optimization. - We create models to simulate, optimize, and control the fulfillment network with the objective of reducing cost while improving speed and reliability. - We support multiple business lanes, therefore maintain a comprehensive and objective view, coordinating solutions across organizational lines where possible.

Are you excited about developing algorithms and models to power Amazon's next generation robotic storage systems? Are you looking for opportunities to build and deploy them on real problems at truly vast scale? At Amazon Fulfillment Technologies and Robotics we are on a mission to build high-performance autonomous systems that perceive and act to further improve our world-class customer experience - at Amazon scale. We are looking for enthusiastic scientists for a variety of roles. The Research team at Amazon Robotics is seeking a passionate, collaborative, hands-on Research Scientist to develop planning and scheduling algorithms to support Amazon's next generation robotic storage systems. The focus of this position workflow optimization and robot task-assignment. It includes designing and evaluating planning and scheduling algorithms using a combination of machine learning and optimization methods as appropriate. This work spans from research such optimal decision making, to policy learning, to experimenting using simulation and modeling tools, to running large-scale A/B tests on robots in our facilities. The ideal candidate for this position will be familiar with planning or learning algorithms at both the theoretical and implementation levels. You will have the chance to solve complex scientific problems and see your solutions come to life in Amazon’s warehouses! Key job responsibilities - Research design - How should solve a particular research problem - Research delivery - Proving/dis-proving strategies in offline data or in simulation - Production studies - Insights from production data or ad-hoc experimentation - Prototype implementation - Building key parts of algorithms or model prototypes A day in the life On a typical day in this role you will work to progress your research projects, meet with engineering, systems, and solutions stakeholders, brainstorm with other scientists on the team, and participate in team processes. You will follow your research projects though the entire life cycle of design, implementation, evaluation, analysis, and will communicate your findings and results through technical papers and reports. You will consult with engineering teams as they incorporate your models and analyses into system and process designs. 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 Our multi-disciplinary science team includes scientists with backgrounds in simulation, planning and scheduling, grasping and manipulation, machine learning, and operations research. We develop novel planning algorithms and machine learning methods and apply them to real-word robotic warehouses, including: * Planning and coordinating the paths of thousands of robots * Dynamic allocation and scheduling of tasks to thousands of robots * Learning how to adapt system behavior to varying operating conditions * Co-design of robotic logistics processes and the algorithms to optimize them Our team also serves as a hub to foster innovation and support scientists across Amazon Robotics. We also coordinate research engagements with academia, such as the Robotics section of the Amazon Research Awards.

The Alexa Smart Home team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment; we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and alerts when something unusual is detected. You can be part of a team delivering features that are highly anticipated by media and well received by our customers. As an Applied Scientist, you will work with other scientists and software developers to design and build the next generation of Smart Home voice control using the latest Large Language Models (LLMs). And, you will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Key job responsibilities - Develop new inference and training techniques to improve the performance of LLMs for Smart Home control and Automation - Develop robust techniques for synthetic data generation for training large models and maintaining model generalization - Mentoring junior scientists to improve their skills, knowledge, and their ability to get things done About the team We are a team of Scientists, Machine Learning Engineers, and Software Developers that work together to make Alexa more insightful and proactive through ambient intelligence, with features like Alexa Hunches that automatically control Smart Home devices. We are interdisciplinary and we act like it. We ask each other questions and value our different perspectives.

Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets. You will work in a fast moving environment to solve business problems as a member of a cross-functional team. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. Key job responsibilities A Senior Economist in this team leads initiatives that make a significant measurable impact on the strategic goals of the business through empowering the PV organization to make smart, long-term decisions through the use of both online (within experiment) and offline metrics (post-predicted) that drive economically sustainable growth for Amazon. They own best in class casual models and metrics that unblock trade-off decisions when business and customer outcomes do not align. Sr. Economist in this team partners with finance to align PV’s economic models with the business financial P&L models, and works closely with Product Managers and Business to bridge the gap between science and business. They partner with data engineers and central teams to standardize economic data definitions and integrate the LTV measures directly in Amazon experimentation tooling. They set the Standard Operating Procedure for the PV LTV measurement systems, provide visibility and explainability into the model outputs to empower users to understand and use them effectively. To be successful in the role, a Senior Economist in PSE must have deep expertise in econometrics and possess a good understanding of strength and weakness of various science approaches.They drive best practices and set standards for metric development process, model calibration, evaluation and governance, and balancing science (i.e. metric fidelity) and engineering constraints. They advise on minimum data requirements for various models, and are able to persuade teams to collect additional observational or experimental data when necessary. They extensively monitor model performance and identify opportunities for improvement in model precision, sensitivity, scalability and operational excellence. About the team Prime Video Content discovery science is a central team which defines customer and business success metrics, models, heuristics and econometric frameworks. The team develops, owns and operates a suite of data science and economic models that govern online and offline decision making systems. The team is responsible for Prime Video’s experimentation practice and continuously innovates and upskills teams across the organization on science best practices. The team values diversity, collaboration and learning, and is excited to welcome a new member whose passion and creativity will help the team continue innovating and enhancing customer experience.