Careers

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. Our work leverages large vision language models (VLMs) with reinforcement learning (RL) and world modeling to solve perception, reasoning, and planning to build useful enterprise agents. 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. Key job responsibilities You will contribute directly to AI agent development in an applied research role to improve the multi-model perception and visual-reasoning abilities of our agent. Daily responsibilities including model training, dataset design, and pre- and post-training optimization. You will be hired as a Member of Technical Staff.

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. Our work leverages large vision language models (VLMs) with reinforcement learning (RL) and world modeling to solve perception, reasoning, and planning to build useful enterprise agents. 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. Key job responsibilities You will lead our efforts to improve the multi-model perception and reasoning abilities of our AI agent in an applied research role. Responsibilities including model training, dataset design, and pre- and post-training optimization. You will be hired as a Member of Technical Staff.

Have you ever wondered how Amazon predicts delivery times and ensures your orders arrive exactly when promised? Have you wondered where all those Amazon semi-trucks on the road are headed? Are you passionate about increasing efficiency and reducing carbon footprint? Does the idea of having worldwide impact on Amazon's multimodal logistics network that includes planes, trucks, and vans sound exciting to you? Are you interested in developing Generative AI solutions using state-of-the-art LLM techniques to revolutionize how Amazon optimizes the fulfillment of millions of customer orders globally with unprecedented scale and precision? If so, then we want to talk with you! Join our team to apply the latest advancements in Generative AI to enhance our capability and speed of decision making. Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfillment Optimization owns and operates optimization, machine learning, and simulation systems that continually optimize the fulfillment of millions of products across Amazon’s network in the most cost-effective manner, utilizing large scale optimization, advanced machine learning techniques, big data technologies, and scalable distributed software on the cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing, and supply. The team has embarked on its Generative AI to build the next-generation AI agents and LLM frameworks to promote efficiency and improve productivity. We’re looking for a passionate, results-oriented, and inventive machine learning scientist who can design, build, and improve models for our outbound transportation planning systems. You will work closely with our product managers and software engineers to disambiguate complex supply chain problems and create ML / AI solutions to solve those problems at scale. You will work independently in an ambiguous environment while collaborating with cross-functional teams to drive forward innovation in the Generative AI space. Key job responsibilities * Design, develop, and evaluate tailored ML/AI, models for solving complex business problems. * Research and apply the latest ML / AI techniques and best practices from both academia and industry. * Identify and implement novel Generative AI use cases to deliver value. * Design and implement Generative AI and LLM solutions to accelerate development and provide intuitive explainability of complex science models. * Develop and implement frameworks for evaluation, validation, and benchmarking AI agents and LLM frameworks. * Think about customers and how to improve the customer delivery experience. * Use analytical techniques to create scalable solutions for business problems. * Work closely with software engineering teams to build model implementations and integrate successful models and algorithms in production systems at large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life You will have the opportunity to learn how Amazon plans for and executes within its logistics ne twork including Fulfillment Centers, Sort Centers, and Delivery Stations. In this role, you will design and develop Machine Learning / AI models with significant scope, impact, and high visibility. You will focus on designing, developing, and deploying Generative AI solutions at scale that will improve efficiency, increase productivity, accelerate development, automate manual tasks, and deliver value to our internal customers. Your solutions will impact business segments worth many-billions-of-dollars and geographies spanning multiple countries and markets. From day one, you will be working with bar raising scientists, engineers, and designers. You will also collaborate with the broader science community in Amazon to broaden the horizon of your work. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career. About the team FPX Science tackles some of the most mathematically complex challenges in transportation planning and execution space to improve Amazon's operational efficiency worldwide at a scale that is unique to Amazon. We own the long-term and intermediate-term planning of Amazon’s global fulfillment centers and transportation network as well as the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfillment network. FPX science team is a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports multiple functional areas across SCOT - Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We disambiguate complex supply chain problems and create innovative data-driven solutions to solve those problems at scale with a mix of science-based techniques including Operations Research, Simulation, Machine Learning, and AI to tackle some of our biggest technical challenges. In addition, we are incorporating the latest advances in Generative AI and LLM techniques in how we design, develop, enhance, and interpret the results of these science models.

Amazon LEO is Amazon’s low Earth orbit satellite network. Our mission is to deliver fast, reliable internet connectivity to customers beyond the reach of existing networks. From individual households to schools, hospitals, businesses, and government agencies, Amazon Leo will serve people and organizations operating in locations without reliable connectivity. The Amazon LEO Infrastructure Data Engineering, Analytics, and Science team owns designing, implementing, and operating systems/models that support the optimal demand/capacity planning function. We are looking for a talented scientist to implement LEO's long-term vision and strategy for capacity simulations and network bandwidth optimization. This effort will be instrumental in helping LEO execute on its business plans globally. As one of our valued team members, you will be obsessed with matching our standards for operational excellence with a relentless focus on delivering results. Key job responsibilities In this role, you will: Work cross-functionally with product, business development, and various technical teams (engineering, science, R&D, simulations, etc.) to implement the long-term vision, strategy, and architecture for capacity simulations and inventory optimization. Design and deliver modern, flexible, scalable solutions to complex optimization problems for operating and planning satellite resources. Contribute to short and long terms technical roadmap definition efforts to predict future inventory availability and key operational and financial metrics across the network. Design and deliver systems that can keep up with the rapid pace of optimization improvements and simulating how they interact with each other. Analyze large amounts of satellite and business data to identify simulation and optimization opportunities. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across LEO. Export Control Requirement: Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum.

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Applied Scientist II will contribute to the development of AI systems. The role requires extending existing scientific techniques and inventing new ones to address specific customer needs at a project level. You should be comfortable working semi-autonomously on difficult problems with visible risks or roadblocks. You'll work closely with technical leaders within the team. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Design and implement solutions that extend or adapt scientific approaches for customer needs at the project level * Deliver components into production that meet high quality standards (efficient, reproducible, testable code) * Produce research reports demonstrating correctness, scholarship, and scientific rigor * Work with product and science teams to deliver impactful AI features * Contribute to operational excellence in the team's deliverables About the team Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. Amazon Connect is the result of the ten years of development that went into building the tools Amazon uses to provide its award winning customer service at massive scale and launching it as a publicly available AWS service. With Amazon Connect, you can create your own cloud-based contact center and be taking calls in minutes. Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Amazon Lex, Amazon Polly, AWS Lambda, Amazon S3 and Amazon Kinesis to provide a truly frustration free, easy-to-use, extensible, and natural customer experience. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them.

As part of the AWS Applied AI Solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use. The Senior Applied Scientist will lead the scientific agenda for AI systems at the product level. The role requires identifying and solving ill-defined problems where no textbook solutions exist, balancing rapid innovation with reliability and compliance. You should be comfortable making decisions with incomplete information and driving solutions in ambiguous problem spaces. You'll work closely with senior technical leaders within the team and across AWS, influencing across multiple teams. We're looking for scientists who can maintain high standards while moving quickly, prioritizing both rapid experimentation and responsible AI development to deliver measurable customer impact. Key job responsibilities * Lead the design, implementation, and delivery of scientifically-complex production solutions that address medium-to-large business problems * Drive your team's scientific agenda and propose new initiatives aligned with customer needs and business problems * Invent new methodologies or paradigms when existing approaches are insufficient * Influence across multiple teams to build consensus on technical direction and scientific approaches * Deliver significant portions of critical-path code that meets high quality standards (efficient, reproducible, testable, maintainable) * Actively mentor and develop other scientists, fostering a culture of scientific excellence About the team Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. Amazon Connect is the result of the ten years of development that went into building the tools Amazon uses to provide its award winning customer service at massive scale and launching it as a publicly available AWS service. With Amazon Connect, you can create your own cloud-based contact center and be taking calls in minutes. Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Amazon Lex, Amazon Polly, AWS Lambda, Amazon S3 and Amazon Kinesis to provide a truly frustration free, easy-to-use, extensible, and natural customer experience. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them.

The Ads Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) team of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. As a Senior Applied Scientist on the team, you will lead measurement solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. For this role, we are seeking a talented scientist with deep expertise in Gen AI to innovate our product portfolio and ease accessibility to actionable insights for our customers. Key job responsibilities - Lead a team of scientists to innovate on state-of-the-art ads measurement solutions leveraging artificial intelligence, causal inference, natural language processing, computer vision, and large language models. - Directly contribute to the end-to-end delivery of production solutions through careful designs and owning implementation of significant portions of critical-path code - Lead the decomposition of problems and development of roadmaps to execute on it. - Set an example for others with exemplary analyses; maintainable, extensible code; and simple, effective solutions. - Influence team business and engineering strategies. - Communicate clearly and effectively with stakeholders to drive alignment and build consensus on key initiatives. - Foster collaborations between scientists to move faster, with broader impact. - Actively engage in the development of others, both within and outside the team. - Regularly engage with the broader scientific community with presentations, publications, and patents. About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions. Team Video: https://youtu.be/zD_6Lzw8raE

As a Senior Data Scientist on our team, you will leverage advanced analytics and machine learning to provide insights and expose risk in our Vulnerability Management systems. You'll develop and deploy sophisticated anomaly detection models, predictive algorithms, and real-time analysis systems that identify flaws in our findings pipeline. Your expertise in statistical analysis, machine learning, large language models, and big data processing will be crucial in building scalable security solutions. You'll collaborate with software engineers, security engineers, business intelligence engineers and managers to: - Analyze large-scale security data using statistical methods and data mining techniques - Create automated systems for real-time pattern recognition and risk assessment - Build data pipelines and ETL processes to handle massive security datasets - Translate complex analytical findings into actionable security insights We use the full power of AWS technologies, including Amazon SageMaker, EMR, and other ML/AI services to monitor, enhance, automate, and report on our security risks. Experience with Python and a strong background in statistical analysis, machine learning, and data mining are essential. We're looking for a new teammate who is enthusiastic, empathetic, curious, motivated, reliable, and able to work effectively with a diverse team of peers. We want someone who will help us amplify the positive & inclusive team culture we've been building. Key job responsibilities - Advising and co-architecting data warehouse solutions to optimize operations and reporting - Building pipelines to automate the business - Running experiments to identify and rectify data and system anomalies - Expanding our existing LLM prompts to automate and baseline security review, and - Analyzing out contextualization outputs to ensure continuous optimal severity assignments About the team Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and exclusive access to coverage of live sports. All customers regardless of whether they have a Prime membership or not, can access programming from subscriptions such as Apple TV, Peacock Premium Plus, HBO Max, FOX One, Crunchyroll and MGM+, as well as more than 900 free ad-support (FAST) Channels, rent or buy titles, and enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! Key job responsibilities - Develop ML models for various recommendation & search systems using deep learning, online learning, and optimization methods - Work closely with other scientists, engineers and product managers to expand the depth of our product insights with data, create a variety of experiments to determine the high impact projects to include in planning roadmaps - Stay up-to-date with advancements and the latest modeling techniques in the field - Publish your research findings in top conferences and journals A day in the life We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences. About the team Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.

Amazon has built a reputation for excellence with recent examples of being named the #1 most trusted company for customers. To deliver on this reputation for trust, Selling Partner Abuse Prevention team is tasked with identifying and preventing abuse for our customers and brand owners worldwide. Selling Partner Fraud and Abuse Prevention is hiring an Applied Scientist who will research and develop innovative machine learning based approaches to predict the near-term future. We are working on advanced research and we support Patent and publishing papers. The Scientist must understand deeply about Machine Learning methods and love extracting, nurturing and transforming high volume of data into actionable business information and making it readily accessible to stakeholders. Key job responsibilities • Lead the research, design, and implementation of innovative AI solutions for selling partner risk assessment and management • Drive the technical vision for applying AI to transform workforce operations in Trust and Store Integrity organization • Develop novel approaches to automate and enhance risk analysis processes using state-of-the-art language models •Partner with business stakeholders to identify high-impact opportunities for AI-driven transformation • Mentor and guide junior scientists while fostering a culture of innovation • Design and implement evaluation frameworks to measure the impact of AI solutions • Ensure responsible AI development with focus on fairness, transparency, and ethical considerations About the team Trust and Store Integrity Science is a new org established in 2024. We are missioned to leverage the fast evolving AI advancements to transform how we prevent bad actors in our stores, across science, engineering, product and program management, and operations.