Senior Applied Scientist, Aws Quick

Amazon Amazon · Big Tech · Santa Clara, CA · Applied Science

Senior Applied Scientist role focused on building next-generation models for intelligent automation within AWS. The role involves designing and implementing neuro-symbolic systems that integrate formal reasoning with GenAI for reliable outcomes, enhancing formal reasoning capabilities for agentic applications, and driving adoption of these solutions across AWS services. It requires end-to-end ownership of the science lifecycle, including research, experimentation, production deployment, and defining performance metrics. The position also involves mentoring junior scientists and contributing to state-of-the-art through publications and patents.

What you'd actually do

  1. Design and implement scalable, production-grade neuro-symbolic systems that integrate formal reasoning with GenAI to deliver reliable, verifiable outcomes for AWS customers.
  2. Collaborate cross-functionally with product, engineering, and science teams as well as external customers to deeply understand pain points, gather requirements, and translate them into neuro-symbolic features that solve real-world problems.
  3. Enhance and extend the capabilities of formal reasoning systems to meet the demands of GenAI and agentic applications — including areas such as hallucination detection, policy verification, and automated guardrails.
  4. Proactively identify and pursue new opportunities to apply formal reasoning solutions across AWS services and customer domains, driving adoption and expanding the impact of neuro-symbolic approaches.
  5. Own the end-to-end science lifecycle — from research and experimentation through production deployment — defining metrics to measure system performance and the real-world impact of neuro-symbolic solutions.

Skills

Required

  • PhD, or Master's degree and 5+ years of applied research experience
  • Experience programming in Java, C++, Python or related language

Nice to have

  • Experience in formal verification, program analysis, constraint-solving, symbolic execution, model checking, SAT/SMT solver implementation and applications, mechanical theorem and/or code-reasoning languages such as Lean

What the JD emphasized

  • PhD, or Master's degree and 5+ years of applied research experience
  • Experience in formal verification, program analysis, constraint-solving, symbolic execution, model checking, SAT/SMT solver implementation and applications, mechanical theorem and/or code-reasoning languages such as Lean

Other signals

  • neuro-symbolic systems
  • formal reasoning
  • GenAI
  • autonomous agents
  • API orchestration
  • hallucination detection
  • policy verification
  • automated guardrails