Applied Scientist, Agentic Automated Reasoning Group

Amazon Amazon · Big Tech · NY +1 · Applied Science

Pioneering next-generation neuro-symbolic tools by fusing AI breakthroughs with cloud scale and automated reasoning expertise. This role involves building scalable formal reasoning solutions, integrating GenAI and Agentic AI, and applying software engineering best practices to production systems. Responsibilities include defining and implementing automated reasoning features, designing and running RL pipelines, experimenting with model tradeoffs, and collaborating cross-functionally. The role also focuses on enhancing formal reasoning systems for GenAI applications, owning the science lifecycle, and advancing the 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. Design and run reinforcement learning pipelines (GRPO, PPO, DPO) to optimize language models for formal reasoning and autoformalization tasks.
  3. Design and run experiments to measure model quality, latency, and cost tradeoffs across model sizes and training strategies.
  4. 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.
  5. 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.

Skills

Required

  • PhD or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience building scalable formal reasoning solutions
  • Experience with GenAI and Agentic AI
  • Experience with reinforcement learning pipelines (GRPO, PPO, DPO)
  • Experience with formal methods
  • Experience with machine learning

Nice to have

  • Experience with neuro-symbolic systems
  • Experience with automated reasoning
  • Experience with AWS
  • Experience with Amazon Bedrock Guardrails

What the JD emphasized

  • production-grade
  • scalable
  • production deployment
  • scalable and efficient approaches
  • production systems
  • scale

Other signals

  • neuro-symbolic systems
  • formal reasoning
  • GenAI
  • agentic AI
  • automated reasoning