Careers

Amazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading technology in generative AI and foundational models. 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 generative AI. Your work will directly impact millions of our customers in the form of products and services that make use of speech, vision and language technology. You will gain hands on experience with Amazon’s heterogeneous speech, text, image and structured data sources, and large-scale computing resources to accelerate advances in machine learning and foundation models. More specifically, you will have the opportunity to impact millions of our customers by researching and building innovative solutions using Agentic AI. Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge generative AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs to create groundbreaking technologies. If you're passionate about shaping the future of AI while making a meaningful impact for customers worldwide, we want to hear from you. A day in the life A day in the life Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon) 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.

As a Senior Applied Scientist for Last Hundred Yards Automation, you will be at the forefront of developing cutting-edge AI and ML solutions that power our autonomous delivery robots. This role combines deep expertise in machine learning, computer vision, and robotics to solve complex challenges in real-world autonomous navigation, obstacle detection, and dynamic path planning. You will work closely with robotics engineers, software developers, and product teams to research, design, and implement sophisticated algorithms that enable safe and efficient last-yard delivery operations. This position requires a unique blend of theoretical knowledge and practical implementation skills, with a focus on transforming research concepts into production-ready solutions that can operate reliably in diverse real-world environments. Key job responsibilities The Senior Applied Scientist will lead the development and implementation of advanced AI/ML models for autonomous navigation, focusing on critical areas such as real-time object detection, semantic scene understanding, and predictive movement planning. You will be responsible for designing and conducting experiments, analyzing complex datasets, and developing novel algorithms to improve robot performance and reliability. The role involves collaborating with cross-functional teams to integrate ML solutions into the robotics platform, optimizing model performance for edge computing, and establishing metrics for continuous improvement. You will also mentor junior scientists, contribute to research publications, and stay current with latest developments in the field. Key activities include developing robust ML pipelines, implementing state-of-the-art deep learning architectures, and creating innovative solutions for challenging problems such as adverse weather navigation, multi-robot coordination, and human-robot interaction. Success in this role requires balancing research excellence with practical implementation, while maintaining a strong focus on safety and reliability in autonomous systems. About the team LMDA (Last Mile Delivery Automation) is a cutting-edge automation system designed to revolutionize the final phase of package delivery, focusing specifically on the last hundred yards from delivery vehicle to customer doorstep. The system integrates autonomous robots equipped with advanced AI/ML algorithms, real-time navigation capabilities, and smart obstacle avoidance technology to efficiently transport packages to their final destination. These robots are designed to navigate various terrains, including sidewalks, building entrances, and residential complexes, while adhering to local safety regulations and maintaining secure delivery protocols. LMDA incorporates cloud-based fleet management, real-time tracking, and dynamic route optimization to ensure seamless coordination between delivery vehicles and robots. The system features a user-friendly interface for both delivery personnel and customers, providing live tracking, delivery notifications, and interactive robot communication. As labor costs rise and delivery volumes increase, LMDA represents a scalable, cost-effective solution that addresses the growing challenges of last-mile delivery while significantly improving operational efficiency and customer satisfaction.

Are you seeking an environment where you can drive innovation? Do you want to apply inference, advanced statistical modeling and techniques to solve world's most challenging problems in? Do you want to play a crucial role in the future of Amazon's Retail business? Do you want to be a part of a journey that develops a new technology from scratch for answering critical business question in Amazon Retail? Every time an Amazon customer makes a purchase, a number of systems are involved: these systems help optimize acquisition, enable a number of purchase options, ensure great , store products so they are available for fast delivery, and minimize package frustration. The Technology (SCOT) Group develops and manages these systems. We are central to Amazon customers' ability to find what they want and get it when they want it. The Consumer Instock Value (CIV) team within Amazon's Supply Chain Optimization Technology (SCOT) Group develops and manages systems that estimate the long-term impact of inventory availability and delivery speed changes at the product level. Our estimates are crucial inputs for multiple production systems across Amazon's supply chain planning, helping teams make critical decisions about inventory management, selection, and placement. Key responsibilities of a Data Scientist in CIV Team include: - Developing new statistical, causal, and machine learning techniques and develop solution prototypes to drive innovation - Working with technical and non-technical customers to design model improvements and communicate results - Collaborating with our dedicated software team to create production implementations for large-scale data analysis - Developing an understanding of key business metrics / KPIs and providing clear, compelling analysis that shapes the direction of our business - Presenting research results to our internal research community - Leading training and informational sessions on our science and capabilities - Your contributions will be seen and recognized broadly within Amazon, contributing to the Amazon research corpus and patent portfolio.

Join our Generative AI focus team to revolutionize Software Development at Amazon Are you ready to be part of a team that's redefining the future of software engineering? Our team is Amazon's ambitious initiative to pioneer AI development practices that will fundamentally transform how we build software at scale. 🎯 Our Mission We're creating the next generation of development tools and practices that will deliver unprecedented efficiency gains through AI-powered automation, intelligent code generation, and advanced developer experiences. 💫 What Makes Us Different * Ground-floor opportunity to shape the future of software development * Direct impact on Amazon's global engineering productivity * Working with the latest AI technologies and large language models * Culture of experimentation and innovative thinking 🔍 What We're Looking For We are looking for world class researchers with experience in one or more of the following areas - autonomous agents, conversational AI, Search and Recommendation, RAG, large multimodal models (especially vision-language models), reinforcement learning (RL) and sequential decision making. 💡 What You'll Do * Design and implement AI-powered development tools and frameworks * Create intelligent automation systems for code generation and testing * Develop new methodologies for AI-assisted software development * Collaborate with teams across Amazon to drive adoption of new tools and practices 🌱 Impact Your work will directly influence how Amazon's vast engineering organization builds software, enabling faster, more reliable software delivery. Join us in writing the next chapter of software engineering history. The future of development is AI, and it starts here. and yes, what you just read was written in 15 seconds using AI... #AmazonTech #AIInnovation #SoftwareEngineering #FutureOfTech

Are you a AI-focused data scientist that wants to think fast, dive deep, and build? We are seeking a data scientists to join our the Amazon Nova Solutions team to work with Foundation Model (FM) teams alongside internal and external Generative AI customers to customize foundation models and build the applications of the future. In this role, you will be the voice of the builder, with ownership for working alongside Amazon businesses to develop GenAI solutions that deliver their immediate business value and realize the future of customer experience. You will help your customers understand best practices and develop new best-practice patterns as you encounter new problem spaces. With your day to day focus on the builder, you will be expected to provide insights to product, science, and engineering on how customers build with our FM's and how we can improve. You will be empowered to invent on behalf of our customers and advocate for their needs throughout design, build, and launch of next gen FM's. You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of foundation models - including evaluation dataset design, metric design, implementation, failure analysis. Ideal candidate has hands on experience with both AI Frameworks (e.g. Strands, LangGraph, CrewAI, DSPy) and model customization tools including PyTorch, TensorBoard, MLFlow/W&B, Bedrock, and SageMaker This position has a high level of visibility, so you will need to be able to communicate clearly and compellingly at all levels of the company. Additionally, you will be responsible for measuring business impact by diving deep into metrics and customer inputs. You should have a positive attitude and strong work ethic; you will work fast and smart, and adapt and iterate quickly. Key job responsibilities - Customer Advisor- Implement, and deploy state of the art machine learning solutions under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers. - Thought Leadership – Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc. - Ensure success in designing, building and migrating applications, software, and services with Amazon Nova FM's, AWS Bedrock, and other AWS GenAI capabilities. - Interact with customers directly to understand their business problems and help them implement durable GenAI systems. - Educate customers on the value proposition of amazon Nova FM ecosystem and showcase the art of possible. - Drive evaluation strategy, metric design, and evaluation data design for real-world use cases - Drive deep architectural discussions and design exercises to create solutions built with Amazon Nova FM's - Author and contribute to AWS customer-facing publications such as whitepapers, workshops, demos and proof of concepts. - Build deep relationships with customer engineering, product, and science leaders. About the team Amazon Nova Applied AI Solutions Team serves as a bridge between Foundation Model science, engineering, and product teams and the internal Amazon teams using these models to deliver business value to Amazon's customers. We help customers build GenerativeAI applications and apply the learning from these engagemetns to help make the Foundation Models better every day.

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 Olympus 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

Do you want to join an innovative team of scientists, engineers and technologists who use AI and machine learning to help Amazon provide the best experience to our Selling Partners by automatically understanding and addressing their challenges, needs and opportunities? Do you want to build agentic systems that transform the business landscape, powered by state-of-the-art AI, such as Large Language Models, Deep Learning, Computer Vision and Causal Modeling, to seamlessly engage with Sellers? Are you excited by the prospect of analyzing and modeling terabytes of data and creating advanced algorithms to solve real world problems? Do you like to build end-to-end business solutions, central to Amazon's tech strategy, that directly impact the profitability of the company and experience of our customers? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Seller Experience Innovation team. Key job responsibilities - Use AI, machine learning and statistical techniques to create the next generation of the agentic tools that empower Amazon's Selling Partners to succeed. - Design, develop and deploy highly innovative AI models to interact with Sellers and delight them with solutions. - Work closely with teams of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. - Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation. - Research and implement novel machine learning and statistical approaches. - Lead strategic initiatives to employ the most recent advances in AI in a fast-paced, experimental environment. - Drive the vision and roadmap for how ML can continually improve Selling Partner experience. - Represent the team as a science leader across Amazon and in public settings. About the team Seller Experience Innovation is a growing team of scientists, engineers and technologists engaged in the research and development of the next generation of AI-driven technology to empower Amazon's Selling Partners to succeed. We draw from many science domains, from foundation models and LLMS to Deep Learning to Computer Vision to Reinforcement Learning, to create solutions that seamlessly and automatically engage with Sellers, solve their problems, and help them grow. Focused on collaboration, innovation and strategic impact, we work closely with other science and technology teams, product and operations organizations, and with senior leadership, to transform the Selling Partner experience.

Are you fascinated by the power of Large Language Models (LLM) and applying Generative AI to solve complex challenges within one of Amazon's most significant businesses? Amazon Selection and Catalog Systems (ASCS) builds the systems that host and run the world’s largest e-Commerce products catalog - it powers the online buying experience for customers worldwide so they can find, discover and buy anything they want. Amazon’s customers rely on the completeness, consistency and correctness of Amazon's product data to make well-informed purchase decisions. We develop LLM applications that make Catalog the best-in-class source of product information for all products worldwide. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries) and multitude of input sources (millions of sellers contributing product data with different quality). You will lead the Amazon Catalog Science team and own devising the strategy and execution plans that power initiatives ranging from: developing tuning artifacts on top of foundational LLMs, training ML models, performing fact extraction, automatic detection of missing product information, active learning mechanisms for scaling human tasks, building applications for distilling product information, building mechanisms to analyze product composition, ingest images, text, and unstructured data to drive deep understanding of products at scale. The right candidate will be a leader who lives and breathes innovation. They'll foster a culture where creative thinking is celebrated and bold ideas can take root. Most importantly, they'll be able to transform this innovative spirit into tangible results, skillfully guiding the team from inspiring vision to real-world impact through careful execution of our strategic roadmap.

We are seeking a passionate, talented, and inventive scientist to join the Amazon AGI team. As an Applied Scientist, you'll be at the forefront of developing intelligent systems that can seamlessly process, understand, and retrieve multimodal information. You'll work on advancing the state-of-the-art in vision-language models and multimodal embeddings, while developing efficient and scalable algorithms for cross-modal retrieval. Your role will involve creating innovative solutions for multimodal ranking and relevance, ultimately building the next generation of multimodal search systems that can understand and process information the way humans do. You'll collaborate with a talented team of researchers and engineers, contribute to research in multimodal search, and see your innovations directly impact millions of customers. If you're passionate about multimodal search and want to shape the future of how machines understand and retrieve information across different modalities, we want to hear from you. Our team values research excellence and encourages publishing in top-tier conferences while maintaining a strong focus on practical applications that benefit real users. Key job responsibilities - As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful search experiences. - Develop state-of-the-art multimodal search technology, including training novel retrieval and ranking models for images/videos, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets. - Leverage Amazon's data and computing resources to accelerate advances in the state of the art in multimodal learning and information retrieval. - Work backwards from customer needs and use that information to make trade-offs between different modeling approaches - Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems - 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

You are a creative and enthusiastic innovator. You are excited to join a new team to start your new chapter with GenAI with advertising. You will focus on designing, developing, and deploying GenAI products at scale that will simplify the internal efficiency, deliver better customer value, automate manual tasks, enhance advertiser experience and accelerate product launches at Twitch Platform. You have deep expertise in Natural Language Processing (NLP), Large Language Models (LLMs), and experience with cloud computing technologies. You can work independently in an ambiguous environment while collaborating with cross-functional teams to drive innovation in the GenAI space. You are an excellent communicator and can explain complex technical concepts to various audiences, can frame loosely defined problems into well-defined GenAI business problems, and is a strategic thinker who can balance research innovation with business requirements and product delivery. Key job responsibilities * Lead the development of enterprise-grade GenAI solutions, using LLMs, embedding models, and multi-modal AI systems. * Design and implement scalable architectures for GenAI applications using AWS services in a production environment. * Closely collaborate with engineer and product teams to identify and implement novel GenAI use cases. * Develop and implement evaluation frameworks for GenAI models. * Author technical papers and present at internal/external conferences. * Mentor Junior scientist and contribute to the team's technical strategy. About the team APM Twitch team is committed to accelerating Twitch’s ad revenue growth by driving innovation in deeply embedded demand-side tech integration, ads sourcing, brand safety and bidder optimization. By innovating new tech solutions, we aim to streamline sales processes and enhance the advertiser experience, enabling scalable, data-driven decisions that align with Twitch’s revenue objectives. We are focused on delivering high-impact, reliable demand solutions that empower advertisers to maximize performance and help position Twitch as a leader in digital ad monetization.