About the role#
Putting an autonomous 40-ton excavator on a live job site requires precise knowledge of its safety and the evidence supporting it. As a Safety Engineering intern, you will explore how formal methods and LLM-assisted proving strengthen these safety arguments. You will work at the intersection of formal methods, statistics, and field robotics to formalize a safety claim, verify a checker in Lean, and evaluate it on real fleet data.
What you'll do#
- Become fluent in our safety case and trace safety claims through hazards, requirements, mitigations, and supporting evidence.
- Build an end-to-end demonstration for a specific claim by defining properties and assumptions, implementing a checker in Lean, proving its correctness, and running it on fleet data.
- Develop checks for assumptions that can be monitored in fleet data and document those requiring other evidence.
- Build audit tooling for LLM-assisted proving, including recording proof dependencies, documenting toolchain trust assumptions, and rejecting unapproved axioms in automated builds.
- Collaborate with Safety, Systems, and Autonomy teams to review formal specifications and improve safety case documentation.
- Document results, limitations, and recommendations for adoption into our review process.
What you'll need#
- Hands-on experience with Lean and mathlib, specifically real analysis or probability.
- Working knowledge of probability and statistics, including distributions, confidence intervals, and tail bounds.
- Ability to translate informal claims into precise specifications and identify their underlying assumptions.
- Experience evaluating LLM-generated code or proofs.
- Familiarity with knowledge graphs or structured document analysis.
- Background in autonomous vehicles, heavy equipment, or other safety-critical robotics.
- Exposure to safety or assurance-case practices like GSN, UL 4600, ISO 13849, or IEC 61508.
- Experience with runtime verification, Rust verification tools such as Aeneas, Verus, or Kani, and differential or property-based testing.
Location & details#
- Location: San Francisco, California
- Term: Summer 2027
- Modality: On-site
- Employment: Full-time intern
- Compensation: Paid position
- Education: Pursuing degrees in Computer Science, Mathematics, Computer Engineering, or Electrical Engineering
About Bedrock Robotics
Bedrock Robotics develops autonomous technology for the construction industry. The company modifies heavy machinery to perform tasks with increased safety and precision. It focuses on infrastructure projects like housing, data centers, and energy facilities. Founded in 2024, the business operates out of San Francisco with 160 employees.
How to get in at Bedrock Robotics
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