Sr. Applied Scientist, AWS Specialists and Partner Prototyping

Core to Amazon's DNA is its methodology around executing experiments and prototypes to find the quickest way to prove new ideas, technologies, and business models in a real-world environment. Experimentation fuels Amazon's innovation. Our team does horizon exploration. We take emerging technology, including our own inventions, build working prototypes with customers and partners, and demonstrate what becomes possible before the rest of the market gets there. Prototyping is how we do the work. Pushing the technology horizon is why we do it. If you are a highly creative problem solver who works to inspire, motivate, and define innovative solutions; are passionate about technology, understand cloud architectures and platforms, and are quick to pick up emerging technologies; are adept at working with customers to experiment with innovative approaches and validate the technical feasibility of solutions, this could be the role for you. As a Senior Applied Scientist you sit directly with customers and partners. You help them envision complex uses of AWS by building working prototypes of specific use cases, tailored to their data, devices, and systems. Engagements run in short build cycles, typically four to six weeks, and are designed to be innovative and evaluative, demonstrating the art of the possible on AWS while proving a credible path to production. You will work across the areas where we are placing our biggest bets. These shift as the technology does, but today they include: - Physical AI and autonomous robotics. World models, vision-language-action (VLA) models, cloud-based and agentic VLA, real-to-sim and sim-to-real pipelines, and agentic control of physical systems. We challenge the assumption that these models have to live only at the edge. - Autonomous scientific discovery. Self-driving labs and instrument intelligence, where agents plan, run, and interpret experiments across fleets of scientific instruments. - Agentic developer intelligence. Multi-agent systems, code agents, and automated research workflows that change how software gets built. - Scaling what we learn. Turning one-off prototypes into reusable patterns and assets the broader field can pick up and run with. You will not just apply these techniques. You will help decide which bets are worth making and prove or disprove them in the open with real customer problems. Key job responsibilities - As a key member of the AWS Specialists and Partner Prototyping team, ensure customer success through hands-on participation producing and demonstrating prototypes on the AWS platform. - Participate in deep architectural and scientific design discussions to ensure prototypes are crafted for successful deployment in the cloud and a credible path to production. - Bring applied science depth to engagements: frame the problem, select and adapt models, design experiments, and judge technical feasibility honestly, including when the answer is that an approach will not work. - Conduct one-to-few and one-to-many training sessions to transfer knowledge to prototyping customers, partners, and internal business partners. - Act as a thought leader for your area of domain expertise across AWS, and share best-practice knowledge among the community. - Author or otherwise contribute to AWS customer-facing publications such as peer reviewed position papers, blogs, and reference patterns. - Act as a technical liaison between customers, service engineering teams, and sales, carrying real-world signal back to the teams building the services. A day in the life No two engagements look the same, which is the point. A typical week might include: - Running a working session with a customer's scientists and engineers to pressure-test an idea and agree on what a prototype needs to prove. - Writing code and training or fine-tuning models in the lab, often against the customer's own data, devices, or robots. - Pairing with a prototyping SA and engagement manager, the standard pod you deliver alongside, to keep the build moving and the scope honest. - Demonstrating a working prototype live and walking stakeholders through what it does, what it does not yet do, and what production would take. - Capturing what you learned as a reusable pattern or publication so the next team does not start from zero. - Spending time on the horizon itself: reading, experimenting with a new model or technique, and forming a point of view on where a bet is heading. You will move between hands-on building and customer-facing explanation constantly. The best people in this role are equally comfortable in a research paper, a code editor, and a room full of executives. About the team 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. 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. 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) conferences, inspire us to never stop embracing our uniqueness. 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. Mentorship and 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. Diverse Experiences Amazon 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. - PhD, or Master's degree and 5+ years of applied research experience - Experience in building machine learning models for business application - Experience programming in Java, C++, Python or related language - Experience using managed ML/AI solutions - Experience conveying complex technical concepts to both technical and business audiences - Experience working with Advanced Compute technologies including, but not limited to: Accelerated Compute, High Performance Compute, Visual/Spatial Compute, and/or IoT. - Experience with vLLM, SGLang, TensorRT or similar platforms in production environments, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution - Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience in machine learning, data mining, information retrieval, statistics or natural language processing - Experience working with Robotics; training and deploying Vision Language Action (VLA) models, World Action models in simulation environment