Careers

The Fulfillment by Amazon (FBA) and Supply Chain by Amazon (SCA) enable third-party sellers to use Amazon's world-class science and logistics infrastructure to supply and fulfill customers worldwide with unprecedented fast delivery promise to customer. In doing so, sellers spend more time building great products, delight customers and grow their business. The FBA team is looking for a Senior Economist with strong machine learning, causal inference, and econometrics skills to join our cross-domain group of economists, applied scientists, research scientists, and data scientists. As a Senior Economist, you will be part of a high-impact team designing and implementing cutting edge machine learning and causal models, incentive mechanisms, experiments to evaluate and (re)design new products and policies, quantify the impact of FBA workflows, seller recommendations, and information on seller decisions and outcomes, while collaborating with business and software teams to solve key challenges facing the worldwide FBA business. We are seeking someone who can thrive in a fast-paced, high-energy, and fun-to-work environment where the team delivers value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their careers. Key job responsibilities - Research and develop machine learning and causal models at scale to solve diverse and complex economic/business problems faced in seller inventory and capacity management systems. - Provide data-driven guidance on strategic questions facing the FBA leadership. - Design and conduct experiments to validate theories and improve understanding of Amazon's third-party seller ecosystem. - Develop mechanisms to align millions of sellers' decisions with those of customers' needs through better coordinating inventory, inbound, and capacity related decisions. - Collaborate with product managers, scientists, and software developers to incorporate models into production processes and influence senior leaders. About the team Sellers play a vital role in Amazon's ecosystem, integral to our mission of offering the Earth's largest selection and lowest prices. FBA is a service that enables third-party sellers to outsource order fulfillment to Amazon, and leverage Amazon's world-class facilities to provide customers Prime delivery promise. By partnering with Amazon, sellers benefit from powerful, cost-effective solutions that leverage our scale and technology, gain access to Prime members worldwide, increase their sales, and have more time to continue inventing amazing products for customers. With commitment to taking on even more of the supply chain and operational complexities on behalf of our selling partners, Amazon introduced Supply Chain by Amazon (SCA), an end-to-end, fully automated suite of supply chain services. This comprehensive solution empowers sellers to quickly and reliably transport products from manufacturing sites to customers worldwide. Amazon Warehousing and Distribution (AWD) is a pivotal service in SCA that provides best-in-class bulk storage and distribution services to sellers, ensuring they remain well-stocked across all their sale and fulfillment channels while reducing the total supply chain costs. The FBA team is the core group in charge of fulfillment, inventory management, pricing, and a diverse range of operational recommendation services for sellers, as well as building the internal resource management systems. We work to learn seller behavior, understand seller experience, build automated assistants to sellers, recommend right actions to sellers, design seller policies and incentives, and develop science products and services that empower third-party sellers to grow their businesses. To do so, we build and innovate science solutions at the intersection of machine learning, statistics, economics, operations research, and data analytics. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA

The Ambient Perception Technology team under Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with computer vision and multimodal perception models for cloud and edge applications. Key job responsibilities As an Applied Scientist with the Ambient Perception Technology team under AGI, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal models with an emphasis on computer vision. Your work will directly impact our customers in the form of products and services that make use of CV technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in within perception domain. A day in the life An Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. About the team The Ambient Perception Technology team has a mission to deliver best in class CV, Audio and multimodal models in support of various edge and cloud applications. We are open to hiring candidates to work out of one of the following locations: Sunnyvale, CA, USA

The Ambient Perception Technology team under Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with computer vision and multimodal perception models for cloud and edge applications. Key job responsibilities As an Applied Scientist with the Ambient Perception Technology team under AGI, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal models with an emphasis on computer vision. Your work will directly impact our customers in the form of products and services that make use of CV technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in AGI in within perception domain. A day in the life A Sr. Applied Scientist with the AGI team will support the science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, a Sr. Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into practice. A Sr. Applied Scientist is expected to work with cross functional stakeholders in driving consensus on technical solutions. About the team The Ambient Perception Technology team has a mission to deliver best in class CV, Audio and multimodal models in support of various edge and cloud applications. We are open to hiring candidates to work out of one of the following locations: Sunnyvale, CA, USA

Prime Video offers customers a vast collection of movies, series, and sports—all available to watch on hundreds of compatible devices. U.S. Prime members can also subscribe to 100+ channels including Max, discovery+, Paramount+ with SHOWTIME, BET+, MGM+, ViX+, PBS KIDS, NBA League Pass, MLB.TV, and STARZ with no extra apps to download, and no cable required. Prime Video is just one of the savings, convenience, and entertainment benefits included in a Prime membership. More than 200 million Prime members in 25 countries around the world enjoy access to Amazon’s enormous selection, exceptional value, and fast delivery. 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! The Marketing Science team aims to drive decision-making on Global Prime Video marketing efforts by delivering sophisticated marketing measurement models. As an Applied Scientist on the team, you will work closely with our business and finance stakeholders, as well as the other members of our team, to shape and deliver a roadmap of models for the team. Your frameworks will be leveraged to inform critical decisions for the business. Key job responsibilities - Create models to predict and optimize future marketing investments and aid strategic decision making. - Build marketing measurement models to assess the impact of marketing investments on customer viewership. - Automate and scale our models to improve efficiency and expand to cover increasing use cases. - Liaise with leaders across business and finance teams to uncover new questions to address through innovative modelling. - Invent new approaches to tackle existing challenges. - Enhance our suite of models to increase rigor and sophistication. We are open to hiring candidates to work out of one of the following locations: Culver City, CA, USA | Seattle, WA, USA

Do you have experience working with NLP, knowledge graphs, or search systems? Do you want a chance to use cutting-edge technologies and work in close collaboration with applied scientists and engineers to deliver value to millions of customers? As a Sr Applied Scientist (Sr AS), you do novel research to improve our graph search solution. You will be able to launch fast and iterate quickly, while publishing your work to external venues. Your team's work will be immediately seen by millions of AGI customers. Key job responsibilities - Research novel modeling techniques to move the state-of-the-art forward - Participate in the design, development, evaluation, and deployment of data-driven models and analytical solutions for machine learning (ML) and natural language (NL) applications - Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems - Work backwards from customer needs and use that information to make trade-offs between different modeling approaches - Report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment - Drive best practices, helping to set high scientific and engineering standards on the team - Promote the culture of experimentation and applied science at Amazon About the team See what our team has to say about working in Santa Barbara in this 2 minute video: https://www.youtube.com/watch?v=hENWxNrobGI Santa Barbara boasts a vibrant tech scene with 40+ startups and established companies. Located just 50 minutes away from Los Angeles’ outer suburbs, Santa Barbara offers other major industries like hospitality, aerospace, healthcare, and more. For partners or families moving to the area, Santa Barbara and neighboring towns Carpinteria, Ventura, and Camarillo offer a range of options for communities to live, learn, and work in. We are open to hiring candidates to work out of one of the following locations: El Segundo, CA, USA | Santa Barbara, CA, USA | Sunnyvale, CA, USA

Have you ever wondered how Amazon predicts when your order will arrive and how we ensure that it actually arrives on at the promised date/time? 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 logistics network including our planes, trucks, and vans sound exciting to you? If so, then we want to talk with you! At Amazon's Supply Chain Optimization Technologies (SCOT), we are tasked with optimizing the fulfilment on customer orders so that we fulfil all orders worldwide in the most intelligent manner while ensuring Amazon customers get their orders on time. Fulfillment Planning & Execution (FPX) Science team within SCOT- Fulfilment Optimization owns and operates OR/ML and simulation systems that continually optimize the distribution of tens of millions of products across Amazon’s warehouses in the most cost-effective manner, utilizing large scale optimization techniques and distributed computing in trying to reduce overall transportation costs while improving the customer experience. We are focused on saving hundreds of millions of dollars using big data technologies, cutting edge science, machine learning, and scalable distributed software on the cloud that automates and optimizes inventory and shipments to customers under the uncertainty of demand, pricing and supply. We’re looking for a passionate, results-oriented, and inventive machine learning scientist who can create and improve models for our outbound transportation planning systems. In addition, you will be working on design, development and evaluation of highly innovative ML models for solving complex business problems in the area of outbound transportation planning systems. You will work closely with our product managers and software engineers to disambiguate complex supply chain problems and create ML solutions to solve those problems at scale. You will directly impact our direct customers, and even play with big data and incredible scale in the background. Watch http://bit.ly/amazon-scot to get the big picture. Key job responsibilities As part of your daily work you will: * Design, development and evaluation of highly innovative ML models for solving complex business problems. * Research and apply the latest ML techniques and best practices from both academia and industry. * Think about customers and how to improve the customer delivery experience. * Use and 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 very large scale. * Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. A day in the life This is a great role for someone who likes to learn new things. You will have the opportunity to learn all about how Amazon plans for and executes within it's logistics network including Fulfillment Centers, Sort Centers, Delivery Stations, and more. In this role, you will be a design and develop Machine Learning models with significant scope, impact, and high visibility. 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. We own Amazon’s global fulfilment center and transportation planning and execution. The team also owns the short-term network planning and execution that determines the optimal flow of customer orders through Amazon fulfilment network. FPX science team contains 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 Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale. We are open to hiring candidates to work out of one of the following locations: Bellevue, WA, USA

Amazon is looking for talented Postdoctoral Scientists to join our Corporate Projects team for a one-year, full-time research position. Corporate Projects is a team that sits within the broader Corporate Development organization at Amazon. We seek to bring net-new, strategic projects to life by working together with customers and evolving projects from ZERO-to-ONE. To do so, we deploy our resources towards proofs-of-concept and pilot programs and develop them from high-level ideas (the ZERO) to tangible short-term results that provide validating signal and a path to scale (the ONE). We work with our customers to develop and create net-new opportunities by relentlessly scouring all of Amazon and finding new and innovative ways to strengthen and/or accelerate the Amazon Flywheel. This Postdoc will work with the group hardware team to perfect the teleoperation interface and continuously test it so that if can evolve to support the program. Key job responsibilities In this role you will: * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. We are open to hiring candidates to work out of one of the following locations: North Reading, MA, USA

Amazon's Sponsored Products advertising business is one of the fastest growing areas in the company. Have you ever wondered what happens behind that “Sponsored” label you see on Amazon? The Sponsored Products Marketplace team creates and optimizes the systems that match advertiser demand (ads) with page supply (placements) using a combination of data-driven product innovation, machine learning, big data analytics, and low latency/high-volume engineering. By the time organic search results are ready, we've processed all of the candidate ads and determined which ones are delivered to the page. We do that billions of times per day, resulting in millions of engagements with products that otherwise might not have been seen by shoppers. The business and technical challenges are significant. Fortunately, we have a broad mandate to experiment and innovate, and a seemingly endless range of new opportunities to build a big, sustainable business that helps Amazon continuously delight all of our customers. We're looking for an innovative and customer-obsessed Applied Scientist who can help us take our products to the next level of quality and performance by creating state-of-the-art models to improve our ability to optimize performance, forecast the impact of advertiser actions, and enable advertisers to scale through impactful features. We embrace leaders with a startup mentality -- those who have a disruptive yet clear mission and purpose, an unambiguous owner's mindset, and a relentless obsession for delivering amazing products. As an Applied Scientist on the Scalable Controls team, you will work alongside business leaders, other scientists, and software engineers to deliver rules that algorithmically manage ads using ML, DL, and R techniques. You will be responsible for bridging the experimental domain with the production domain by building robust and efficient computational pipelines to scale up models, keeping the models fresh, and ensuring that real-world corner cases are handled correctly. You'll own significant products and features from inception through launch, and will work with Product Managers, other Scientists, and Engineers to make your efforts wildly successful. You will lead the science program for our team, providing input to strategic decision making on topics such as program direction/vision, roadmap, and staffing. If this sounds like your sort of challenge, read on. Characteristics indicative of success in this role: • Highly analytical: You solve problems in ways that can be backed up with verifiable data. You focus on driving processes, tools, and statistical methods which support rational decision-making. •Technically fearless: You aren't satisfied by performing 'as expected' and push the limits past conventional boundaries. Your dial goes to '11'. • Engaged by ambiguity: You're able to explore new problem spaces with unique constraints and non-obvious solutions. • Team obsessed individual contributor: You help grow your team members to achieve outstanding results. You've learned that big plans generally involve collaboration and great communications. • Quality obsessed: You recognize that professional scientists build high quality model development and evaluation frameworks to ensure that their models can provably meet launch criteria, or efficiently iterate in the framework until they do. • Humbitious: You’re ambitious, yet humble. You recognize that there’s always opportunity for improvement. You use introspection and feedback from teammates and peers to raise the bar. Key job responsibilities • Apply machine learning and analytical techniques to create scalable solutions for business problems • Work closely with software engineering and product teams across the organization to drive model implementations and new feature creations • Work closely with business stakeholders to identify opportunities for current model improvements and new models to significantly benefit the business bottom-line • Collaborate with scientists within the Ads organization as well as other parts of Amazon to share learnings move the state-of-the-art forward • Establish scalable, efficient, automated processes for data analyses, model development, model validation and model implementation • Research and implement novel machine learning and statistical approaches We are open to hiring candidates to work out of one of the following locations: Toronto, ON, CAN

Amazon launched the Generative AI Innovation Center in June 2023 to help AWS customers accelerate innovation and business success with Generative AI (https://press.aboutamazon.com/2023/6/aws-announces- generative -ai -innovation center). This Innovation Center provides opportunities to innovate in a fast-paced organization that contributes to breakthrough projects and technologies that are deployed across devices and the cloud. As a data scientist, you are proficient in designing and developing advanced generative AI solutions to solve diverse customer problems. You'll work with terabytes of text, images, and other types of data to solve real-world problems through Gen AI. You will work closely with account teams and ML strategists to define the use case, and with other ML scientists and engineers on the team to design experiments and find new ways to deliver customer value. The selected person will possess technical and customer-facing skills that will enable you to be part of the AWS technical team within our solution providers ecosystem/environment as well as directly to end customers. You will be able to lead discussion with customer and partner staff and senior management. A day in the life Here at AWS, we embrace our differences. We are committed to promoting our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in more than 190 branches around the world. We have innovative benefit offerings and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced by our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and build trust. About the team Work/life balance Our team highly values work-life balance. It's not about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe that finding the right balance between your personal and professional life is fundamental to lifelong happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own work-life balance. Mentoring and career growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and mandates and are building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one guidance and thorough but gentle code reviews. We care about your career growth and strive to assign projects based on what will help each team member become a more well-rounded engineer and enable them to take on more complex tasks in the future. We are open to hiring candidates to work out of one of the following locations: Sao Paulo, SP, BRA

Amazon launched the Generative AI Innovation Center (GAIIC) in Jun 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. As a Data 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 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 them 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. A day in the life A day in the life Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. About the team Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future. We are open to hiring candidates to work out of one of the following locations: Mexico City, DIF, MEX