Staff Applied Research Scientist

Snowflake Snowflake · Data AI · CA-Menlo Park, United States · Engineering

Staff Applied Research Scientist at Snowflake to lead research projects applying formal methods, program analysis, automated reasoning, and AI (including code generation and modeling) to cloud data platform problems. The role involves translating research into shipped capabilities, partnering with engineering and product, influencing roadmaps, training teams, and maintaining field expertise through publications and contributions. Requires a PhD, depth in formal methods, distributed systems, software engineering, and AI/ML, with 8+ years of experience applying theoretical computer science to large-scale systems.

What you'd actually do

  1. Lead research projects that apply formal methods, program analysis, automated reasoning, and AI-driven techniques (including code generation and modeling) to real problems in our cloud data platform.
  2. Translate research ideas into prototypes, then into shipped capabilities that move concrete business metrics — quality, velocity, reliability, and operational performance at scale.
  3. Partner closely with engineering leaders, product managers, and key customers to identify high-leverage opportunities and turn them into deliverables.
  4. Influence the engineering and product roadmap; advise leaders on which research directions are pragmatic and which are not.
  5. Train and uplevel engineering teams on new methods, and scale those methods across the organization.

Skills

Required

  • PhD (or equivalent research experience) in Computer Science or a closely related field
  • Depth across formal methods (model checking, theorem proving, SAT/SMT, program verification, type systems, or program analysis)
  • Depth across distributed systems (designing, reasoning about, or verifying large-scale concurrent and distributed systems)
  • Depth across software engineering fundamentals
  • Practical experience applying modern ML, including LLMs, to systems problems such as code generation, synthesis, or automated reasoning
  • 8+ years applying theoretical computer science to large-scale software systems (ideally cloud data platforms, distributed systems, or developer infrastructure)
  • Demonstrated ability to drive company-level initiatives in partnership with engineering and product leadership
  • Track record of technical contribution to the field (publications, open-source work, patents, or comparable evidence of impact)
  • Comfortable in a fast-paced, ambiguous environment

Nice to have

  • experience with Iceberg and Polaris
  • experience with Snowpark, Dynamic Tables, cross-region replication, time travel, or zero-copy cloning

What the JD emphasized

  • PhD (or equivalent research experience)
  • 8+ years applying theoretical computer science to large-scale software systems
  • Track record of technical contribution to the field — publications, open-source work, patents, or comparable evidence of impact.
  • impact is measured by what ships

Other signals

  • applying formal methods, program analysis, automated reasoning, and AI-driven techniques to cloud data platform problems
  • translating research ideas into prototypes and shipped capabilities
  • improving correctness, reliability, and engineering velocity at scale