Careers

At Amazon, we strive every day to be Earth’s most customer-centric company. Selling Partner Support Engagement (SPSE) Science delivers on this by building AI-enhanced experiences that provide world class support to our global network of selling partners. We are building applications at the forefront of GenAI applications, tackling the challenges caused by the volume, diversity, and complexity of our selling partner's needs. Do you want to join a team of scientists with critical problem solving skills who are innovating on behalf of our customers using statistical inference, natural language processing, computer vision and generative AI? Are you interested in helping us redefine what world class support can be in an age of automation and AI, while prizing human empathy and ingenuity? Are you excited by the prospect of your solutions resulting in large-scale impact while getting a chance to research at the forefront of AI innovation? The SPSE Science Team is looking for an Applied Scientist to build statistical, machine learning and GenAI solutions (AI agents, LLM fine-tuning) that help us understand and solve our most challenging problems. We need to better understand our Sellers and the problems they face, to augment our human workforce with smarter tools, to anticipate problems so that we are prepared to deal with them and to automatically diagnose and resolve issues. In this role, you will have ownership of the end-to-end development of solutions to complex problems and you will play an integral role in strategic decision-making. You will also work closely with engineers, operations teams and product owners to build ML pipelines, platforms and solutions that solve problems of defect detection, automation, and workforce optimization. Key job responsibilities - Use state-of-the-art Machine Learning and Generative AI techniques to create the next generation of tools that empower Amazon's Selling Partners and Support Associates to succeed. - Design, develop and deploy models that either interact with end users or automate entire workflows. - Work closely with teams of scientists and software engineers to drive online model implementations with impactful features through A/B testing. - Establish scalable, efficient, automated processes for large scale data analyses, model benchmarking, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Participate in strategic initiatives to employ the most recent advances in ML in a fast-paced, experimental environment. About the team Selling Partner Support Engagement Science (Titans Science) is a growing team of scientists engaged in the research and development of the next generation of ML-driven technology to empower Amazon's Selling Partners to succeed. We strive to radically simplify the seller experience, making it easy to accomplish critical tasks such as launching new products, understanding and complying with Amazon’s policies and taking actions to grow their business. Scientists on the team get an opportunity to learn the state of the art end-to-end ML tooling and infrastructure offered through AWS and other open source technology stacks. The complexity of our work also give scientists an opportunity to successfully publish research in leading journals and conferences. We value 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. Additionally, the team fosters an inclusive and learning culture, inspiring us to embrace our uniqueness. We highly value individual growth; you will also find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

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 ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. 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.

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 ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. 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.

The Amazon Connect Interactive AI and Engagement organization was formed in April 2025 to bring together Contact Lens, Q in Connect, and Flows/Lex into one organization, responsible for weaving native-AI across the Connect application experiences delivered to end-customers, agents, and managers/supervisors. We are reimagining customer engagement to enable companies to deliver proactive and personalized experiences (in websites, mobile apps, and traditional contact center channels including voice, messaging, and email) that discern and resolve end-customers' intent before problems ever arise. To succeed, we need a unified science strategy and approach to power 'AI-throughout' customer experiences that leverage humans in the loop when required to meet business goals. We seek to hire a Director of Applied Science who will define and execute that strategy, and organization required. This leader will push the technical boundaries in generative AI science, shaping the industry, while influencing and leading key product investments across Connect service teams and leadership. The business opportunity is substantial. We are executing to be the leader irrespective of the ultimate balance between proactive end-customer self-service and agent-assisted workloads. To do so, science innovation will be pivotal to help achieve our ambitious goals, differentiating Amazon Connect from our competitors. Key job responsibilities The Director of Applied Science will lead us to propose and deliver an organizational plan that is aligned to a unified science strategy. This science strategy will enable data-driven, AI-powered continuous optimization across self-service, agent assistance, and manager assistance workloads. This leader will inherit an existing applied science team, and possibly (strategy dependent) a data integrations team engineers. We believe that the strategy this leader defines will require additional applied scientists. Beyond direct team ownership, this leader will be responsible for cross-AWS science collaboration with Bedrock, AGI, Q, and Transcribe organizations.

Application deadline: Dec 17, 2025 The Amazon Web Services Professional Services (ProServe) team is seeking an experienced Delivery Practice Manager (DPM) to join our ProServe Shared Delivery Team (SDT) at Amazon Web Services (AWS). In this role, you'll manage a team of ProServe Delivery Consultants while supporting AWS enterprise customers through transformative projects. You'll leverage your IT and/or Management Consulting background to serve as a strategic advisor to customers, partners, and internal AWS teams. As a DPM you will be responsible for building and managing a team of Delivery Consultants and or Engagement Managers working with customers and partners to architect and implement innovative solutions. You’ll routinely engage with Director, C-level executives, and governing boards, whilst being responsible for opportunity capture and driving engagement delivery. You’ll work closely with partner teams; drive business development initiatives through thought leadership; provide portfolio guidance and oversight; and meet and exceed customer satisfaction targets. As a DPM you are primarily focused directly or through their teams, on understanding and defining business outcomes for customers by building trust, identifying applicable AWS Professional Services offerings, and creating proposals and SOW’s. Your experience gained leading teams within the technology sector, will equip you with the ability to optimize team performance through implementing tailored people development plans, ensuring your teams are aligned to customer needs, and have the skills and capacity to address customer outcomes. Possessing the ability to translate technical concepts into business value for customers and then talk in technical depth with teams, you will cultivate strong customer, Amazon Global Sales (AGS), and ProServe team relationships which enables exceptional business performance. DPMs success is primarily measured by consistently delivering customer engagements by supporting sales through scoping technical requirements for an engagement, delivering engagements on time, within budget, and exceeding customer expectations. They will hold the Practice total utilization goal and be responsible for optimizing team performance. The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries. This position requires that the candidate selected must currently possess and maintain an active TS/SCI security clearance. The position further requires that, after start, the selected candidate have the ability to obtain and maintain an active TS/SCI security clearance with polygraph or commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities As an experienced Professional Services Delivery Manager, you will be responsible for: - Building and managing a high-performing team of Delivery Consultants - Collaborating with Delivery Consultants, Engagement Managers, Account Executives, and Cloud Architects to deploy solutions and provide input on new features - Developing and overseeing the implementation of innovative, forward-looking IT strategies for customers - Managing practice P&L, ensuring on-time and within-budget delivery of customer engagements - Driving business development initiatives and exceed customer satisfaction targets About the team Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, 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 (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 role will contribute to developing the Economics and Science products and services in the Fee domain, with specialization in supply chain systems and fees. Through the lens of economics, you will develop causal links for how Amazon, Sellers and Customers interact. You will be a key and senior scientist, advising Amazon leaders how to price our services. You will work on developing frameworks and scaleable, repeatable models supporting optimal pricing and policy in the two-sided marketplace that is central to Amazon's business. The pricing for Amazon services is complex. You will partner with science and technology teams across Amazon including Advertising, Supply Chain, Operations, Prime, Consumer Pricing, and Finance. We are looking for an experienced Principal Economist to improve our understanding of seller Economics, enhance our ability to estimate the causal impact of fees, and work with partner teams to design pricing policy changes. In this role, you will provide guidance to scientists to develop econometric models to influence our fee pricing worldwide. You will lead the development of causal models to help isolate the impact of fee and policy changes from other business actions, using experiments when possible, or observational data when not. Key job responsibilities The ideal candidate will have extensive Economics knowledge, demonstrated strength in practical and policy relevant structural econometrics, strong collaboration skills, proven ability to lead highly ambiguous and large projects, and a drive to deliver results. They will work closely with Economists, Data / Applied Scientists, Strategy Analysts, Data Engineers, and Product leads to integrate economic insights into policy and systems production. Familiarity with systems and services that constitute seller supply chains is a plus but not required. About the team The Stores Economics and Sciences team is a central science team that supports Amazon's Retail and Supply Chain leadership. We tackle some of Amazon's most challenging economics and machine learning problems, where our mandate is to impact the business on massive scale.

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 Principal 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.

Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the The Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI Platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with worlds’ leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for Applied Scientists passionate about helping startups use GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. Key job responsibilities * Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities * Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production * Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization * Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience * Provide customer and market feedback to product and engineering teams to help define product direction * Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements About the team AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

We are seeking a Senior Applied Scientist to drive innovation in machine learning and artificial intelligence for Amazon's autonomous delivery systems. In this role, you will develop novel algorithms and models that power our autonomous vehicle perception, prediction, and decision-making systems. You will combine rigorous scientific methodology with practical engineering to solve complex problems in real-world autonomous navigation and delivery. Key job responsibilities - Design and develop advanced machine learning models and algorithms for autonomous vehicle systems - Lead research initiatives in areas such as computer vision, sensor fusion, behavioral prediction, and path planning - Transform research concepts into production-ready solutions that meet strict safety and performance requirements - Develop novel approaches to solve complex technical challenges in autonomous navigation - Create and implement metrics and evaluation frameworks to measure model performance - Collaborate with engineering teams to integrate ML solutions into the autonomous vehicle stack - Publish research findings and represent Amazon at technical conferences - Mentor junior scientists and contribute to building a culture of scientific excellence A day in the life A typical day for a Senior Applied Scientist begins with analyzing experimental results from recent model deployments. They might spend the morning developing new deep learning architectures for sensor fusion or improving prediction models for pedestrian behavior. Mid-day could involve collaborating with engineering teams to optimize model performance and reduce inference latency. Afternoon activities might include designing experiments to validate new approaches, reviewing research papers for potential application, and participating in technical discussions to solve challenging problems in perception or planning. They would regularly engage in code reviews, documentation of methods, and mentoring of team members. The role requires balancing innovative research with practical implementation, ensuring that scientific advances translate into reliable autonomous system capabilities. About the team The Applied Science team within Amazon's Last Mile Delivery Automation organization focuses on developing cutting-edge machine learning solutions for autonomous systems. We work at the intersection of computer vision, deep learning, robotics, and control systems to create robust and scalable algorithms that enable safe autonomous operation. Our team combines expertise from diverse scientific backgrounds to tackle fundamental challenges in perception, prediction, and decision-making. We collaborate closely with software engineering teams to deploy our solutions across Amazon's autonomous delivery fleet.

Amazon Agentic AI is looking for world class scientists to join its newly created org focusing on agentic AI. This group is entrusted with developing core natural language processing, agents, generative AI, deep learning and machine learning algorithms for AWS, with a focus on code development, broadly defined. You will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually new solutions. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS Q, a generative AI–powered assistant for enterprise computing, and work with other acclaimed engineers and world famous scientists. As an Applied Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs. You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and business outcome. About the team 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. 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.