About The Position

As part of the Agentic WorkSpaces organization, we empower millions of professional users—spanning enterprises, research institutions, and government agencies—through AWS WorkSpaces, a cloud-based desktop and application management platform. Our mission is to redefine productivity for users navigating complex legacy application environments by deploying agentic AI solutions that bridge the gap between generative AI and real-world enterprise workflows. We combine Amazon’s deep operational expertise with a relentless focus on innovation to deliver AI experiences that are intuitive, scalable, and transformative. Where legacy systems pose unique challenges, we become the trusted partner for customers seeking to automate, optimize, and future-proof their workflows. The Senior Applied Scientist will lead the development of LLM-driven agentic systems tailored to AWS WorkSpaces environments. This role demands pioneering scientific approaches to solve unresolved problems at scale, balancing rapid iteration with rigorous evaluation. Success hinges on your ability to design, implement, and validate AI solutions that empower users to work smarter in legacy-heavy ecosystems.

Requirements

  • 5+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

Nice To Haves

  • Experience working with cross-functional teams across business development, marketing, operations, product development, legal, etc.
  • Expertise in computer vision or computer-use automation (e.g., UI interaction, screen understanding) to tackle unique legacy system challenges.
  • Experience fine-tuning LLMs for domain-specific applications, optimizing for efficiency, safety, and enterprise requirements.

Responsibilities

  • Architect agentic AI systems that leverage LLMs, computer vision, and computer-use techniques to interact with legacy applications within AWS WorkSpaces.
  • Build evaluation frameworks to quantify agent performance, reliability, and user impact in real-world, unstructured environments.
  • Fine-tune and deploy domain-specific LLMs for workspace use cases, ensuring efficiency, safety, and alignment with enterprise requirements.
  • Collaborate cross-functionally with peer teams (e.g., troubleshooting, onboarding, security) to embed AI capabilities across the WorkSpaces product suite—from strategic visioning to hands-on implementation.
  • Drive operational excellence by delivering high-quality, production-ready science components that meet Amazon’s standards for robustness, reproducibility, and scalability.

Benefits

  • sign-on payments
  • restricted stock units (RSUs)
  • health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
  • 401(k) matching
  • paid time off
  • parental leave
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