System Safety Engineer, Autonomy Trucking

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · SDS Systems Engineering

This role focuses on defining and managing the safety architecture and requirements for autonomy software and hardware for L4 SDS product lines in the automotive industry. It involves performing safety analyses (FMEA, FTA, STPA), working with verification and validation, and promoting a safety culture. While it deals with autonomous systems and ML safety, the core function is system safety engineering rather than direct AI/ML model development.

What you'd actually do

  1. Derive and manage safety concepts, requirements and specifications for autonomy software and hardware for L4 SDS product line
  2. Lead efforts for development of safety architecture
  3. Perform safety analysis such as FMEA, FTA, STPA and derive relevant safety work and products
  4. Work with verification and validation to ensure requirements are being verified throughout the development process
  5. Contribute to the overall safety case of the final product

Skills

Required

  • 2+ years of experience in a System Safety Engineering role or Functional Safety Engineering role
  • MS/BS degree in Computer Science, Electrical, Mechanical, Systems Engineering or equivalent required
  • Expertise in mechanical, electrical, and software engineering
  • Experience with ADAS, autonomous systems and robotics
  • Knowledge of existing standards and regulations relevant in the automotive industry, esp. ISO 26262, ISO 21448, ISO/DPAS 8800, UL4600 and ongoing activities with regards to ML and safety
  • Experience with driving safety requirements across the V model from architecture to requirements generation, implementation and verification and validaiton
  • Mastery of strong collaboration with other teams, customers, and companies to ensure high quality deliverables

Nice to have

  • Prior work in either autonomous vehicles or ADAS
  • Understanding of metrics and how to tie evidence to a safety case
  • Project management and leadership experience in the AV industry
  • Experience in the AV and robotics fields
  • Experience with the safety of ML systems

What the JD emphasized

  • safety architecture
  • safety concepts
  • safety requirements
  • safety analysis
  • safety case
  • safety performance
  • safety practices
  • safety of ML systems