Careers

Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced groundbreaking devices like Fire tablets, Fire TV, Amazon Echo, and the Astro household robot. What will you help us create? As a Principal Controls Scientist, you will be responsible for developing solutions to control complex electromechanical systems. You will take responsibility for developing models, performing analysis, and producing algorithms for the control and estimation of robotic systems that guide and inform mechanical and electrical designs, software implementation, and other software modules that affect overall device safety and performance. You will demonstrate cross-functional interaction to accomplish your goals. You will play a role in defining processes and methods to improve the productivity of the entire team. You will interface with Amazon teams outside your immediate organization to identify leverage opportunities with minimized dependencies. You will investigate applicable academic and industry research applications, identify and initiate investigations of production technologies, prototype and test solutions to support product features, and design and validate production designs that deliver an exceptional user experience. Key job responsibilities - Produce models and simulations of complex, high degree-of-freedom dynamic electromechanical systems - Design estimation and control algorithms that achieve performance targets within hardware and software constraints - Hands-on prototyping and testing on physical systems in the lab - Influence hardware and software design decisions owned by other teams to optimize system-level performance - Define key performance indicators and allocate error budgets across hardware and software modules - Perform root cause analysis of system-level failures and distinguish between hardware/software failures and hardware/software mitigations - Balance objectives of safety, performance, and cost in architectural design decisions - Lead cross-functional teams (controls, firmware, perception, planning, sensors, mechanical, electrical, etc.) to solve complex system integration issues - Translate business requirements to engineering requirements and identify trade-offs and sensitivities - Mentor junior and senior engineers in good design practice; actively participate in hiring of new team members About the team The Dynamic Systems and Control team develops models, algorithms, and code to bridge hardware and software development teams and bring robotic products to life. We contributed to Amazon Astro (https://www.amazon.com/Introducing-Amazon-Astro/dp/B078NSDFSB) and Echo Show 10 (https://www.amazon.com/echo-show-10/dp/B07VHZ41L8/), along with several new technology introductions and unannounced products currently in development.

This is a unique opportunity to join a small, high-impact team working on AI agents for health initiatives. You will lead the crucial data foundation of our project, managing health data acquisition, processing, and model evaluation, while also contributing to machine learning model development. Your work will directly influence the creation and improvement of AI solutions that could significantly impact how individuals manage their daily health and long-term wellness goals. If you're passionate about leveraging data and developing ML models to solve meaningful problems in healthcare through AI, this role is for you. You'll work on large-scale data processing, design annotation workflows, develop evaluation metrics, and contribute to the machine learning algorithms that drive the performance of our health AI agents. You'll have the chance to innovate alongside healthcare experts and data scientists. In this early-stage initiative, you'll have significant influence on our data strategies and ML approaches, shaping how they drive our AI solutions. This is an excellent opportunity for a high-judgment data scientist with ML expertise to demonstrate impact and make key decisions that will form the backbone of our health AI initiatives. Key job responsibilities Be the complete owner for health data acquisition, processing, and quality assurance Design and oversee data annotation workflows Collaborate on data sourcing strategies Lead health data acquisition and processing initiatives Manage AI agent example annotation processes Develop and implement data evaluation metrics Design, implement, and evaluate machine learning models for AI agents, with a focus on improving natural language understanding and generation in health contexts A day in the life You'll work with a cross-disciplinary team to source, evaluate, and leverage health data for AI agent development. You'll shape data acquisition strategies, annotation workflows, and machine learning models to enhance our AI's health knowledge. Expect to dive deep into complex health datasets, challenge conventional data evaluation metrics, and continuously refine our AI agents' ability to understand and respond to health-related queries.

Ring is looking for a Senior Applied Science Manager to lead the development of computer vision algorithm on the Edge. In this role, you will be the leader of our passionate, talented, and inventive scientists, to develop industry-leading Computer Vision (CV), Multimodal, and AI and drive them successfully to production for the benefit of millions of Amazon Devices users. This is a unique, high visibility opportunity for a leader who wants to have business impact, and dive deep into computer vision problems. We are particularly interested in candidates with experience productizing edge-based computer vision systems. Key job responsibilities As a Senior Manager, Applied Science, you bring structure to ambiguous business problems and use science, logic, and practical experience to decompose them into straightforward, scalable solutions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems; you're interested in learning; and you acquire skills and expertise as needed. The ideal candidate is a strong, creative and highly-motivated Scientist with hands-on experience in leading multiple research and engineering initiatives. You balance technical leadership with strong business judgment to make the right decisions about technology, tools, and methodologies.

Amazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/) and Security Hub (https://aws.amazon.com/security-hub/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity. The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services. Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work. Key Responsibilities: - Invent, implement, and deploy state of the art machine learning algorithms and systems for information security applications. - Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment. - Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services. - Report results in a scientifically rigorous way. - Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for. - Work closely with a mentor to expand your career with AWS 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 we 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 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. 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. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. This team is part of AWS Utility Computing: 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.

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

Are you passionate about leveraging data to deliver actionable insights that impact daily marketing activities at Amazon? The Customer Targeting team in Amazon is seeking an Applied Scientist to join our team to develop models for optimizing the performance of Amazon’s marketing initiatives across channels and advertising formats. You have experience applying modern machine learning methods to answer key business questions, make strategic and tactical recommendations for change, and work with business leaders to drive these to production. You are entrepreneurial and able to work in a highly collaborative environment. This role requires an individual with strong quantitative modeling skills and experience using statistical methods. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment. You will be expected to: - Leverage knowledge of statistics and optimization to frame decision-making problems for determining marketing spends across channels. - Predict future customer behavior and business conditions through machine learning and predictive modeling. - Use analytical and predictive techniques to build models for optimizing targeting. - Present proposals and results in a clear manner backed by data and coupled with actionable conclusions.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP organization's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Our team, SP Off-Search Supply Expansion and Creative (SPEC) team is responsible for Sponsored Products experiences expansion for store display placements, 1P surfaces such as Home Page, Checkout pages like HUC, TYP, Cart and shared placements on AAX owner slots. The team also owns UX for all Off Search placements. Spec owns SP Firebird Core Infra team working on SP creative optimization and personalized ASIN faceout We are looking for a passionate Senior Applied Scientist who has technical expertise in information retrieval, Natural Language Processing (NLP), and Large Language Models (LLM). In addition to having hands-on experience in building ML-based solutions, an ideal candidate should be able to create and articulate a customer-centric science vision, show willingness to continuously learn about new scientific approaches, and enjoy operating in startup-like environment. Key job responsibilities • Lead business, science and engineering strategy and roadmap for Sponsored Products Off-Search Supply Expansion and Creative optimization. • Drive alignment across organizations for science, engineering, and product strategy to achieve business goals. • Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize the shopper experience and deliver long term value for Amazon and advertisers • Develop state of the art experimental approaches and ML models.

Amazon is looking for a motivated individual with strong analytical and algorithmic skills and practical experience to join the Modeling and Optimization (MOP) Routing Science team. Your main focus will be on developing and improving our last-mile experience, with emphasis on algorithmic and analytical work. We are looking for candidates with proven ability to design, implement, and evaluate state-of-the-art solutions to large-scale optimization problems, working closely with software development engineers. The position requires strong background in combinatorial optimization, algorithms, algorithm engineering, and data structures, particularly as it applies to vehicle routing and related problems. Familiarity with Data Science and Machine Learning techniques is a plus. You will also play an integral role in the network planning, modeling, and analysis that will improve the efficiency and cost effectiveness of global fulfillment operations. You will identify and evaluate opportunities to reduce variable costs by improving the transportation network topology, inventory placement, transportation operations and scheduling, fulfillment center processes, and the execution to operational plans. You will also improve the efficiency of capital investment by helping plan the location and deployment of fixed assets. Finally, you will help create the metrics to quantify improvements to the fulfillment costs (e.g., transportation and labor costs) resulting from the application of these optimization models and tools.

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! In this role, you will invent science and systems for Transactional Video on Demand and Channels, including machine learning-based pricing and promotion systems. You will work with a team of scientists and product managers to design customer-facing products, and you will work with technology teams to productize and maintain the associated solutions. We are looking for an applied scientist to join our interdisciplinary team of Data Scientists, Applied Scientists, Economists, Data Engineers and Software Engineers. The ideal candidate combines machine learning expertise with the ability to deploy algorithms into production. You have deep knowledge of recommender systems and/or personalization models and experience applying them to Amazon-scale data. You understand tradeoffs between business needs and model complexity, and you take calculated risks in developing rapid prototypes and iterative model improvements. You are excited to learn from and alongside seasoned scientists, engineers, and business leaders. You are an excellent communicator and effectively translate technical findings into production systems and business action (and customer delight). Key responsibilities As an Applied Scientist on this team, you will: - Develop and implement recommender models for studio partners and customers; - Perform hands-on analysis and modeling of enormous datasets to develop insights that increase customer engagement and monetization; - Run experiments, gather data, and perform statistical analysis; - Collaborate with tech and engineering teams to develop and optimize production systems; - Research new and innovative machine learning approaches; - Work with other scientists to raise the science and coding bar across Prime Video. About the team 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 programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.

The AdsEcon Team is looking for an Applied Scientist II to help and be part of a team to put state-of-the-art causal inference research into production. AdsEcon is a cross-functional team of Economists, Applied Scientists, Data Scientist and Engineers, with the charter of developing moonshot science solutions for Amazon Advertising. We favor projects that are ambitious, ambiguous, and risky. We use a combination of econometrics, machine learning, and randomized experiments to build disruptive initiatives for all our Advertising products. We also generate insights to guide Amazon Advertising strategy, providing direct support to the high level leaders. Key job responsibilities If you have a experience with building causal inference and other machine learning solutions at scale this is the job for you. Key responsibilities of Applied Scientist include the following: - Partnering with economists and senior team members to drive science improvements and implement technical solutions at the state-of-the-art of machine learning and econometrics - Design, implement, prototype, deploy, and maintain large-scale Causal/ML models. Models are often deployed in partner's teams code base, requiring good communication skills and collaborative spirit. - Build interpretable statistical models and analyze experiment results to answer questions that will drive high impact decisions across Amazon.