Careers

Amazon is looking for talented Postdoctoral Scientists to join our Robotics team for a one-year, full-time research position. Postdoctoral Scientists will innovate in key areas of computer vision and manipulation challenges in Amazon warehouses. The Amazon Robotics team seeks to automate the picking activities in Amazon AR Sortable FCs by retrofitting into existing stations. The team develops robotic manipulators, both the related hardware and software (including machine learning approaches). The team was formed in 2022 and is based in Berlin. Our team focuses on solving computer vision and manipulation challenges in Amazon warehouses. For example, how can robots interact with the fabric pods used to store items. The technical challenges include 3D scene understand for items in clutter, identification of target items in the scene, and placement and/or removal of target items. As the solution space is open ended, the team is looking for postdoc candidates who are excited to apply and advance the state-of-the-art algorithms to this domain. 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.

Are you passionate about solving complex wireless challenges that impact millions of customers? Join Amazon's Device Connectivity team who are revolutionizing how wireless technology shapes the future of consumer electronics. As a Wireless Research Scientist, you'll be at the forefront of developing solutions that enhance the connectivity and reliability of millions of customer devices. Your expertise will drive the creation of next-generation wireless technologies, from concept to implementation, directly shaping the future of Amazon's product ecosystem. In this role, you'll tackle complex electromagnetic challenges head-on, leveraging your analytical prowess and deep understanding of wireless principles. You'll collaborate with world-class scientists and engineers, applying machine learning and statistical analysis to optimize system performance and create scalable, cost-effective solutions for mass production. Your impact will extend beyond the lab, as you transform research concepts into practical features that delight our customers. You'll influence product roadmaps, drive critical technical decisions, and play a key role in accelerating our product development lifecycle. Key job responsibilities As a Wireless research scientist, you will use your experience to initiate wireless design, development, execution and implementation of scientific research projects. Working closely with fellow hardware dev, scientists and product managers, you will use your experience in modeling, statistics, and simulation to design new hardware, customer modeling and evaluate their benefits and impacts to cost, connectivity use cases, reliability, and speed of productization Ability to work and connect concepts across various engineering fields like EMC design, desense, antenna, wireless communication and computational electromagnetics to solve complex and novel problems Experience in combinatorial optimization, algorithms, data structures, statistics, and/or machine learning that can be leveraged to develop novel wireless designs that can be integrated and mass produced on products. This position requires superior analytical thinking, and ability to apply their technical and statistical knowledge to identify opportunities for wireless/EM applications. You should be able to mine and analyze large data, and be able to use necessary programming and statistical analysis software/tools to do so. Ability to leverage ML techniques for design optimization and performance modeling that influence technology integration and productization of novel consumer products. A day in the life Invent • You invent and design new solutions for scientifically-complex problem areas and identify opportunities for invention in existing or new business initiatives. • You expertly frame the scientific approach to solve ambiguous business problems, distinguishing between those that require new solutions and those that can be addressed with existing approaches. • You focus on business and customer problems that require scientific advances at the product level. Your research solutions set a strong example for others. You work efficiently and routinely delivered the right things. • You show good judgment when making trade-offs between short- and long-term customer, business, and technology needs. • You drive your team’s scientific agenda by proposing new initiatives and securing management buy-in. • You lead the writing of internal documents or external publications when appropriate for your team and not precluded by business considerations. • Your work consistently delivers significant benefit to the business. What you deliver could be functional, such as a software system or conceptual, such as a paper that advances scientific knowledge in a specific field or convinces the business to focus on a particular strategy. Implement • You are self-directed in your daily work and require only limited guidance for confidence checks. • You define and prioritize science or engineering specifications for new approaches. • You independently assess alternative technologies or approaches to choose the right one to be used by your system or solution with little guidance. You may own the delivery of solutions for an entire business application. • You ensure accuracy in your process abstractions, models, and simulation results. • Your solutions are inventive, maintainable, scalable, extensible, accurate, and cost-effective (e.g., you know where to extend or adapt methods). • Your solutions are creative and of such a high quality that they can be handed off with minimal rework. Influence • You are a key influencer in team strategy that impacts the business. You make insightful contributions to team roadmaps, goals, priorities, and approach. • You build consensus on larger projects and factor complex efforts into independent tasks that can be performed by you and others. • You actively recruit and help others by coaching and mentoring in your organization (or at your location). • You are involved and visible in the broader scientific communities (internal or external) as a subject matter expert. For example, you may give guest lectures, review scientific work of others, serve as a Program Committee member in conferences, or serve as a reviewer for journal publications. • You contribute to the broader internal and external scientific communities. About the team 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 innovative devices like Fire tablets, Fire TV and Amazon Echo. What will you help us create?

Are you excited about leveraging state-of-the-art Deep Learning, Recommender Systems, Information Retrieval, Natural Language Processing algorithms on large datasets to solve real-world problems? As an Applied Scientist Intern, you will based in Amazon's Melbourne office working in a fast-paced, cross-disciplinary team of experienced R&D scientists. You will take on complex problems, work on solutions that leverage existing academic and industrial research, and utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even deliver these to production in customer facing products. Please note: This internship is a duration of 6 months full time with a start date in Jan-March 2026. The successful intern is required to be based in Melbourne and relocation allowance will be provided if you are based outside of Melbourne. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Machine Learning and Information Retrieval - Contribute to research that could significantly impact Amazon operations - Collaborate with a diverse team of experts in a fast-paced environment - Collaborate with scientists on writing and submitting papers to top conferences, e.g. NeurIPS, ICML, KDD, SIGIR - Present your research findings to both technical and non-technical audiences Key Opportunities: - Work in a team of ML scientists to solve recommender systems problems at the scale of Amazon - Access to Amazon services and hardware - Become a disruptor, innovator, and problem solver in the field of information retrieval and recommender systems - Potentially deliver solutions to production in customer-facing applications - Opportunities to be hired full-time after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!

AWS Agentic AI is looking for a world-class Applied Scientist with a strong deep learning background to help build industry-leading Agentic AI (models, systems, and applications). Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Understanding (NLU), AI assisted code development, reasoning and planning with LLMs, LLM training and fine-tuning, and Applied Machine Learning (ML). As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in Agentic AI. Your work will directly impact millions of our customers in the form of products and services that make use AI technology. You will gain hands on experience with Amazon’s heterogeneous text, structured data sources, and large-scale computing resources to accelerate advances in language understanding. We are hiring in all areas of Agentic AI: NLP/NLU, Conversational AI, Reasoning and Planning, LLM model training, and application development. Key job responsibilities - Develop breakthroughs is agentic architecture in areas such as autonomy, self-validation, and continuous learning. - Mentor and guide junior scientists. - Develop technology strategy and roadmap supporting product development - Develop prototypes for key technology, oversee the productization of the prototype, and develop critical assessment for the prototype - Write technical reports summarizing R&D progresses and communicate such progresses with stakeholders About the team The Amazon Web Services (AWS) Agentic AI team uses generative AI and foundation models to advance application development. In the space of software development and life cycle management, we see the application of AI anywhere: from the IDE to web-based tools and services, AI helps engineers work many applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.

MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Data Scientist II Job Location: New York, New York Job Number: AMZ8839670 Position Responsibilities: Design and implement scalable and reliable approaches to support or automate decision making throughout the business. Apply a range of data science techniques and tools combined with subject matter expertise to solve difficult business problems and cases in which the solution approach is unclear. Acquire data by building the necessary SQL / ETL queries. Import processes through various company specific interfaces for accessing Oracle, RedShift, and Spark storage systems. Build relationships with stakeholders and counterparts. Analyze data for trends and input validity by inspecting univariate distributions, exploring bivariate relationships, constructing appropriate transformations, and tracking down the source and meaning of anomalies. Build models using statistical modeling, mathematical modeling, econometric modeling, network modeling, social network modeling, natural language processing, machine learning algorithms, genetic algorithms, and neural networks. Validate models against alternative approaches, expected and observed outcome, and other business defined key performance indicators. Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production. Position Requirements: Master’s degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and one year of experience in the job offered or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent degree in Statistics, Applied Mathematics, Economics, Engineering, Computer Science, or a related field and five years of progressive post-baccalaureate experience in the job offered or a related occupation as equivalent to the Master’s degree and one year of experience. Must have one year of experience in the following skill(s): (1) building statistical models and machine learning models using large datasets from multiple resources; (2) writing SQL scripts for analysis and data migration; and (3) applying specialized modelling software including R, Python, or MATLAB. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation 40 hours / week, 8:00am-5:00pm, Salary Range$160,125/year to $207,500/year Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000

Amazon is seeking an exceptional Applied Scientist to join AGI Info Content team. In this role, you will be at the forefront of developing and enhancing the intelligence of AmazonBot crawler and content processing. The team is a key enabler of Amazon's AGI initiatives such as data pipelines for Nova model training and collecting data for AGI Info grounding services. Our systems operate on web scale. This requires great combination of innovation to utilize all SOTA ML techniques in combination with model optimization to operate on 100k+ requests/decision per second. Your work will directly impact the quality and efficiency of our data acquisition efforts, ultimately benefiting millions of customers worldwide. Key job responsibilities Design, develop, and implement advanced algorithms and machine learning models to improve the intelligence and effectiveness of our web crawler and content processing pipelines. Collaborate with cross-functional teams to identify and prioritize crawling targets, ensuring alignment with business objectives Analyze and optimize crawling strategies to maximize coverage, freshness, and quality of acquired data while minimizing operational costs as well as dive deep into data to select the highest quality data for LLM model training and grounding. Conduct in-depth research to stay at the forefront of web acquisition and processing. Develop and maintain scalable, fault-tolerant systems to handle the vast scale of Amazon's web crawling operations Monitor and analyze performance metrics, identifying opportunities for improvement and implementing data-driven optimizations Mentor and guide junior team members, fostering a culture of innovation and continuous learning

Are you excited about leveraging state-of-the-art Computer Vision algorithms and large datasets to solve real-world problems? Join Amazon as an Applied Scientist Intern and be at the forefront of AI innovation! As an Applied Scientist Intern, you'll work in a fast-paced, cross-disciplinary team of pioneering researchers. You'll tackle complex problems, developing solutions that either build on existing academic and industrial research or stem from your own innovative thinking. Your work may even find its way into customer-facing products, making a real-world impact. Please note: This internship is a duration of 6 months full time with a start date in Jan-March 2026. The successful intern is required to be based in Melbourne and relocation allowance will be provided if you are based outside of Melbourne. Key job responsibilities - Develop novel solutions and build prototypes - Work on complex problems in Computer Vision and Machine Learning - Contribute to research that could significantly impact Amazon's operations - Collaborate with a diverse team of experts in a fast-paced environment - Collaborate with scientists on writing and submitting papers to Tier-1 conferences (e.g., CVPR, ICCV, NeurIPS, ICML) - Present your research findings to both technical and non-technical audiences Key Opportunities: - Collaborate with leading machine learning researchers - Access cutting-edge tools and hardware (large GPU clusters) - Address challenges at an unparalleled scale - Become a disruptor, innovator, and problem solver in the field of computer vision - Potentially deliver solutions to production in customer-facing applications - Opportunities to become an FTE after the internship Join us in shaping the future of AI at Amazon. Apply now and turn your research into real-world solutions!

Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like Echo, Fire Tablets, Fire TV, and other consumer devices. We are looking for exceptional scientists to join our Applied Science team to help build industry-leading technology with multimodal language models for various edge applications. Key job responsibilities - Collaborate with cross-functional engineers and scientists to advance the state of the art in multimodal model evaluations for devices - Invent and develop novel multimodal evaluation benchmarks against product use cases - Design and develop tools for human-in-the-loop model evaluation experiments - Partner with engineering teams to integrate evaluation methods across the deployment pipeline - Work closely with scientists, compiler engineers, data collection, and product teams to advance evaluation methods A day in the life As an Applied Scientist with the Silicon and Solutions Group Edge AI team, you'll contribute to innovative methods for evaluating new product experiences, conduct experiments, explore new algorithms, and discover ways to enrich our customer experiences. You'll have opportunities to collaborate across teams of engineers and scientists to bring algorithms and models to production. About the team Our Edge AI science team brings together our unique skills and experiences to deliver state-of-the-art multimodal AI models that enable new experiences on Amazon devices.

We are open to hiring candidates to work out of one of the following locations: Arlington, VA, USA | Austin, TX, USA | Herndon, VA, USA | New York, NY, USA | Seattle, WA, USA At AWS Security, we're on a mission to revolutionize how we manage security vulnerabilities at scale for host operating systems and third party software. We're seeking a Senior Applied Scientist specializing in generative AI to join our team and lead the charge in developing provable security solutions that protect our customers and empower our builders. In this role, you'll be at the forefront of addressing one of the most critical challenges in cloud security today: managing security risks due to vulnerable code in host operating systems or third party software. With the increasing frequency and sophistication vulnerabilities, your work will be crucial in safeguarding AWS environments against vulnerabilities that can arise from external components integrated into our infrastructure. You'll leverage your expertise in generative AI and machine learning to develop innovative approaches for identifying, assessing, and remediating security risks in third-party software. Your solutions will help bridge the gap between rapid innovation and robust security practices, ensuring that the software packages our builders use are not only efficient but also comply with AWS security standards. As a key member of our team, you'll collaborate closely with cross-functional teams to integrate your scientifically-validated security measures into existing workflows. Your work will directly impact AWS's ability to respond quickly and efficiently to vulnerabilities, addressing challenges such as package naming ambiguity between internal and external sources. We're looking for someone who can think strategically about both mid-term tactical improvements and long-term security innovations. You'll be instrumental in establishing a data-driven decision framework that will guide our security measures, ensuring they're not only effective but also optimized for builder efficiency. Your role extends beyond just technical innovation. As a senior member of the team, you'll be a thought leader in the field of AI-driven security, contributing to the broader Amazon Science community and potentially publishing your findings in top-tier scientific venues. You'll also mentor team members, sharing your expertise and helping to cultivate the next generation of security innovators at AWS. This position offers a unique opportunity to make a substantial impact across AWS, contributing to the overall resilience and trustworthiness of our security programs. Your work will be central to maintaining customer trust and delivering secure, delightful customer experiences across all of Amazon's products and services. If you're passionate about solving complex challenges, have a deep understanding of generative AI and machine learning, and are excited about the prospect of shaping the future of cloud security, we want to hear from you. Join us in our mission to set new standards for security through AI innovation at Amazon. Key job responsibilities 1. Lead research and development of generative AI solutions to address security challenges in Vulnerability Management. 2. Develop and implement data-driven decision frameworks to analyze patterns in the package environment and quantify the impact of security improvements on builder productivity. 3. Collaborate closely with cross-functional teams to integrate scientifically-validated security measures into existing workflows. 4. Design and conduct experiments to solve complex security problems 5. Develop scalable, AI-driven solutions to efficiently respond to vulnerabilities in software packages. 6. Create and implement long-term strategic plans for integrating generative AI into AWS security practices. 7. Publish research findings in scientific venues and contribute to the broader Amazon Science community. 8. Mentor team members and provide expertise on a range of machine learning topics related to security. A day in the life You will be joining the AWS Vulnerability Management (AVM) team, focusing on vulnerability remediation at the host operating systems and third party software. We must scale through utilization of Amazon AI tooling and machine learning modeling. Your day to day is solve security problems that causes builders not to patch (or update software) in time, and how we leverage data we have (or need) to build security solutions to resolve these problems. 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.

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. As an Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities - Participate in the design, development, evaluation, deployment and updating of data-driven models for computer vision applications. - Research and implement the state-of-the-art computer vision and Vision Language models algorithms. - Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices - Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors.