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  • Emplois similaires à : Principal System Safety Engineer
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Senior System Engineer- AI SafetyRhoda AI • Mountain View, California, United States
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Senior System Engineer- AI Safety

Rhoda AI
  • US
    Mountain View, California, United States
  • US
    Mountain View, California, United States
Postuler Maintenant

À propos

At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $450M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality.
Summary This is a Senior MTS position reporting directly to the Head of Safety and Certification. The AI System Safety Engineer will own the safety assurance lifecycle for the AI system powering our humanoid robot platform operating in environments alongside humans. This role sits at the intersection of AI, functional safety, and robotics — responsible for ensuring that the robot's AI-driven perception, planning, and control behaviors meet the requirements of the broader humanoid robot safety standard ecosystem. You will assess risks introduced by model-driven behaviors, define AI safety requirements, lead verification of AI model safety properties, and build the evidence packages needed for formal certification. The role requires a technical executor with a bias for action, impeccable rigor, and the ability to drive cross-disciplinary teams. The candidate must demonstrate deep technical credibility.
Core Responsibilities
Lead AI-specific hazard identification and risk assessment sessions using STPA (Systems-Theoretic Process Analysis), FMEA, and scenario-based analysis to surface AI-related failure modes of perception
Assess risks introduced by AI model updates and retraining cycles, including regression of safety-critical behaviors
Identify unsafe control actions that can arise from AI decision‑making across all robot operating modes: autonomous navigation, collaborative manipulation, human handoff, and degraded/safe-state operation
Establish safety requirements for AI model inputs, outputs, confidence thresholds, uncertainty quantification, and out-of-distribution detection
Develop test cases for verification and validation of AI safety
Define, engineer, deploy and employ system safety validation cells instrumented to collect artifacts to be reviewed by safety assessor
Maintain full traceability from safety goals through AI system requirements to test cases and evidence artifacts
Required Qualifications
B.S. Computer Science, Systems Engineering or Robotics
Experience designing AI-based safety systems for complex electromechanical products with significant safety aspects
Demonstrated understanding of AI/ML failure modes relevant to physical systems — distributional shift, model uncertainty, unsafe generalization — and practical methods for measuring and mitigating them
Experience in STPA
Hands‑on experience in Verification and Validation of AI‑focused safety requirements
Preferred Extras
Experience in humanoid robots, automotive, autonomous mobile robots (AMR)
Experience in applying ISO/IEC TS 22440 or ISO/PAS 8800
Certified Functional Safety Engineer in IEC 61508 or ISO 26262
Experience in automotive ADAS or robotics collision avoidance
Experience with vision, time of flight cameras, laser sensors
In-depth understanding of safety-critical architectures for algorithms
Direct experience building structured Safety Cases for learned or adaptive AI systems deployed on physical platforms
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  • Mountain View, California, United States

Compétences linguistiques

  • English
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