Careers

The Alexa Connections team is building the worlds most trusted AI assistant, that helps get things done and creates moments of joy. We build LLM-powered, next-generation communication features that help customers connect within the household with features like announcements and drop-In, and with people they care about with features like calling, emailing and texting. Using GenAI we proactively personalize every single connection moment whether its connecting with grandparents or communicating with kids teachers, and you can do it all hands free with Alexa! We are hiring a mature Sr. Manager of Applied Science who is an entrepreneurial big thinker that invents and then biases towards action to solve highest priority customer problems. Our portfolio initiative range from highly confidential innovations to data driven quality problems that needs sciences solutions. You will be leading a team of scientists and partnering with product, engineering and design organizations to building on the latest AGI/LLM systems. If you are holding out for an opportunity to: - Join a leadership group that moves fast towards big audacious goals - Lead an organization to balance solving towards problems while working towards the long term vision - Be surrounded by super passionate mission driven colleagues who will challenge you to grow every day - Solve difficult challenges using your expertise in science to invest practical solutions - Create applications at a massive scale used by millions of people - Work with AGI/LLM systems to deliver real experiences, not just research And you are experienced with… - Driving applied science projects end-to-end from ideation, analysis, prototyping, development, metrics, and monitoring - Conducting deep analyses on massive user and contextual data sets - Proposing viable modeling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results - Designing, developing, and maintaining scalable ML models and LLM's with automated training, validation, monitoring and reporting - Staying familiar with the field and apply state-of-the-art ML techniques to NLP and related optimization problems - Publishing peer-reviewed scientific papers in top journals and conferences And you constantly look for opportunities to… - Innovate, simplify, reduce waste, and increase efficiency - Use data to make decisions and validate assumptions - Automate processes otherwise performed by humans - Learn from others and help those around you grow ...then lets chat! Key job responsibilities As a senior leader, you will play a critical role in elevating the team’s scientific and technical rigor, identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. You will establish a long-term vision for continued scientific innovation, setting strategic goals to future-proof the organization’s technical stacks and ML/LLM frameworks to support new and emerging business objectives. Additionally, you will grow talents, fostering a culture of excellence and continuous learning to enhance the organization’s ability to solve complex problems.

Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities Responsible for building the infrastructure + SDKs needed to integrate web applications and their associated tasks into a production RL environment with significant concurrency limits and operational requirements. Core Engineering: Architect and deliver robust software solutions throughout the development lifecycle Design and implement applications using modern TypeScript and Python Build and deploy cloud-native applications and RESTful APIs Engineer and optimize high-performance systems at scale Collaboration & Leadership: Collaborate with cross-functional stakeholders to deliver aligned features Mentor junior engineering staff Maintain technical documentation and architectural decision records

Amazon One Medical is hiring a Actuarial Analyst. Actuarial rigor is one of the keys to our success. This candidate will responsible primarily for several critical workstreams which include analysis of Medicare Advantage and Accountable Care Organization data, design and implement an actuarially sound monthly reserving process for Total Medical Expense (TME) estimation, and lead continuous evaluation of TME performance compared to plan expectations. Key job responsibilities -Analysis of Medicare Advantage and Accountable Care Organization data primarily -Medical economics reporting and ad-hoc analysis relating to cost of care management -Medicare Risk score projections and premium estimation -Design and implement an actuarially sound monthly reserving process for Total Medical Expense (TME) estimation -Lead continuous evaluation of TME performance compared to plan expectations -Coordinate with the finance team on future TME projections that are refreshed monthly and provided quarterly for forecasting and planning -Support month end financial and accounting processes for relevant actuarial estimates. -Value based care contracting support and ongoing financial and risk analysis. -Support ongoing actuarial support for outside auditor review of financial estimates and results. -Design studies to monitor the suitability of the completion factor estimates. -Lead continuous evaluation of risk based funding and scoring performance compared to plan expectations. -Complete the evaluation of stop-loss coverage and manage third party vendors -Analyze and develop new to market assessments and modeling which includes future Medicare geographic expansion and enhancements / changes to other market segments (Commercial potentially)

If you have ever bought or sold anything on Amazon, you have touched Amazon Marketplace. Amazon’s Marketplace business is one of the largest in the world. We are now in 23 countries. We are growing fast, with customers in many more countries. Amazon’s platform is the engine that powers Amazon’s Marketplace businesses, and Sellers rely on this platform and our support to start selling on Amazon and to grow their business. Amazon Marketplace enables millions of Sellers worldwide to list hundreds of millions of products and manage orders for inventory across dozens of different categories and languages. While working with millions of Sellers worldwide, we constantly strive to improve the selection for Customers and the capabilities of our platform for Sellers. The Seller Fulfillment Services (SFS) team is looking for a motivated and innovative Applied Scientist with strong analytical skills and practical experience to join our science team. As a key member of the SFS science team, you will provide expertise that helps accelerate the business. You will build science solutions that will help us to provide our customers with the largest selection of merchants at the lowest, and the most reliable delivery service regardless of the seller. You will research, design and improve on the models that will impact Amazon’s customer directly. You will be working in a highly collaborative environment partnering with various science, product management, engineering, operations, finance, business intelligence and analytics teams to develop science models to solve business problems. You will need to understand the business requirements and translate them into complex analytical outputs. You will design tests to explain performance of the models from impact on customer and cost perspective. You will create ML models to capture features impacting performance. You should be comfortable building prototypes, testing and improving them given the feedback from the real time data. You should be able to present your model and findings to a various range of stakeholders. An ideal candidate will be an expert in the areas of machine learning, operations research, and statistics. With expertise in applying theoretical models in an applied environment relying heavily on the latest advances in machine learning, optimization, stochastic modeling, and engineering. The candidate will be expected to work on numerous aspects, such as feature engineering, modeling, probabilistic modeling, hyper-parameter tuning, scalable inference methods and latent variable models. Challenges will involve dealing with very large data sets and requirements on throughput. Key job responsibilities - Design, implement, test, deploy, and maintain innovative science solutions to accelerate our business. - Create experiments and prototype implementations of new learning algorithms and prediction techniques - Collaborate with scientists, engineers, product managers, and stakeholders to design and implement software solutions for science problems - Use best practices to ensure a high standard of quality for all of the team deliverables

Join us in the evolution of Amazon’s Seller business! The Selling Partner Growth organization is the growth and development engine for our Store. Partnering with business, product, and engineering, we aim to accelerate the growth of Sellers by providing tools and insights that enable them to make better and faster decisions at each step of selection management. To accomplish this, we offer intelligent insights that are both detailed and actionable, allowing Sellers to introduce new products and engage with customers effectively. We leverage extensive structured and unstructured data to generate science-based insights about their business. Furthermore, we provide personalized recommendations tailored to individual Sellers' business objectives through agentic experience to drive adoption and facilitate growth. These insights and recommendations are integrated into our direct seller-facing products, including Amazon Brand Analytics (ABA), Product Opportunity Explorer (OX), and Growth Agent. We are looking for a talented and passionate Senior Applied Science Manager to lead our key AI initiatives to drive our seller and hence store growth. In this role, you will spearhead the development of a suite of scientific models designed to capture the CX signals to recognize unmet customer demand, identify high value selections in its early stages and generate prioritization signals for high value sellers. You will also lead the development of next generation of agentic experience to surface valuable selection information to sellers directly. The successful candidate will work closely with Product Managers (PM), User Experience (UX) designers, and engineering teams to deliver products that drive significant business impacts in Seller businesses. Key job responsibilities As a Senior Manager for Applied Science, you will: * Lead and grow a team of applied scientists working on selection success * Drive the technical vision for implementing ML and LLM-based solutions to provide the agentic selection recommendation experience and drive seller growth * Drive scalable ML/DL/RL and LLM solutions that can handle the breath and complexity of guiding Amazon 3P sellers to success at scale * Collaborate with product, engineering, and business teams to define and execute the technical roadmap * Translate complex customer problems into practical ML solutions * Monitor and improve key performance metrics for seller performance, ease of use and satisfaction * Stay current with the latest developments in ML/DL/LLM research and identify opportunities for implementation

Are you driven by the challenge of solving complex problems that directly impact the safety and well-being of millions of Amazon Associates worldwide? Do you want to push the boundaries of AI to build innovative solutions that make workplaces safer and more efficient? If so, we invite you to join our WHS DataTech team as an Applied Scientist and take your career to the next level! At WHS DataTech, we leverage Large Language Models (LLMs), Computer Vision, and AI-driven innovations to develop industry-leading solutions that proactively enhance workplace safety. Our work spans real-time risk assessment, predictive analytics, and AI-powered insights, all aimed at creating a safer work environment at scale. As an Applied Scientist specializing in LLMs and Computer Vision, you will play a pivotal role in shaping our next-generation safety solutions. You’ll be at the forefront of innovation, designing and implementing AI-powered features that redefine workplace safety. Your work will drive strategic decisions, optimize system architecture, and influence best practices, ensuring our technology remains industry-leading. Key job responsibilities - Apply LLM model to analyze complex unstructured datasets and extract meaningful insights. - Collaborate with software engineers to implement and deploy machine learning (LLM or CV) solutions. - Conduct experiments and evaluate model performance, iterating and improving as needed. - Stay up-to-date with the latest advancements in machine learning and related fields. - Collaborate with cross-functional teams to understand business needs and identify areas for application of machine learning. - Present findings and recommendations to stakeholders and contribute to the overall research and development strategy. 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 WHS DataTech is a multidisciplinary team of scientists and engineers dedicated to building AI-powered solutions that improve workplace safety across Amazon. We work at the intersection of large-scale data, advanced machine learning, and computer vision, delivering innovations that enhance decision-making, streamline operations, and protect millions of associates worldwide. Our collaborative culture emphasizes scientific rigor, engineering excellence, and a strong mission focus on creating safer, more efficient workplaces.

Want to work on frontier, world class, AI-powered experiences for health customers and health providers? The Health Science & Analytics group in Amazon's Health Store & Technology organization is looking for a Senior Manager of Applied Science to lead a group of applied scientists and engineers to work hand in hand with physicians to build the future of AI-powered healthcare experiences. We have an ambitious roadmap which includes scaling recently launched products which are already delighting products and the opportunity to build disruptive, new experiences. This role will be responsible for leading the science and technology teams driving these key innovations on behalf of our customers. Key job responsibilities - Independently manage a team of scientists and engineers to sustainably deliver science driven products. - Define the vision and long-term technical roadmap to achieve multi-year business objectives. - Maintain and raise the science bar of the team’s deliverables and keep the broader Amazon Health Services organization apprised of the latest relevant technical developments in the field. - Work across business, clinical, and technical leaders to disambiguate product requirements and socialize progress towards key goals and deliverables. - Proactively identify risks and shape the technical roadmap in anticipation of industry trends in emerging AI subfields.

Amazon launched the Generative AI Innovation Center (GAIIC) in June 2023 to help AWS customers accelerate the use of Generative AI to solve business and operational problems and promote innovation in their organization (https://press.aboutamazon.com/2023/6/aws-announces-generative-ai-innovation-center). GAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud. Key job responsibilities As an Applied Science Manager in GAIIC, you'll partner with technology and business teams to build new GenAI solutions that delight our customers. You will be responsible for directing a team of data/research/applied scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, and deliver state-of-the-art solutions to customer’s business and mission problems. Your team will be working with terabytes of text, images, and other types of data to address real-world problems. The successful candidate will possess both technical and customer-facing skills that will allow you to be the technical “face” of AWS within our solution providers’ ecosystem/environment as well as directly to end customers. You will be able to drive discussions with senior technical and management personnel within customers and partners, as well as the technical background that enables them to interact with and give guidance to data/research/applied scientists and software developers. The ideal candidate will also have a demonstrated ability to think strategically about business, product, and technical issues. Finally, and of critical importance, the candidate will be an excellent technical team manager, someone who knows how to hire, develop, and retain high quality technical talent. AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. About the team AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud. 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 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.

We are looking for a science leader who is able to provide structure around complex business problems, work with machine learning scientists to estimate and validate their models on large scale data, and who can help business and tech partners turn the results of their analysis into policies, programs, and actions that have a major impact on Amazon’s business. We are looking for creative thinkers who can combine a strong economic toolbox with a desire to learn from others, and who know how to execute and deliver on big ideas. At the senior level, we expect you be able to own the development of scientific models and to manage, in close collaboration with scientists and engineers, the data analysis, modeling, and experimentation that is necessary for estimating and validating your model. You will need to work with our business partners to communicate the properties of your analysis/modeling and be able to work to incorporate their feedback and requests into your project. Experience in applied economic analysis is essential, and you should be familiar with modern tools for data science and business analysis. About the team The Stores Economics and Science (SEAS) organization uses economics, statistics, and machine learning to understand and design the complex economy of Amazon’s network of buyers and sellers. We are an interdisciplinary team, committed to use of cutting edge technology and leveraging the strengths of engineers and scientists to build solutions for some of the toughest business problems at Amazon. Our team is composed in equal parts of software engineers and scientists trained in diverse fields including ML, robotics, computer vision (CV), natural language processing (NLP), distributed systems and econometrics. Our mission is to drive adoption of AI science and technology across Amazon by partnering with business teams on science-heavy problems, incubating products with high AI research risk, reducing friction and manual effort with AI tooling, and raising the scientific bar across all teams at Amazon.

About Amazon Advertising: Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place. About our team: Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods. Key job responsibilities We are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring state-of-the-art research to raise the bar within the team.