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.
This is a Staff position reporting directly to the Head of Safety and Certification. We're looking for 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 and the appetite to grow into a leadership position as the safety organization scales.
What You'll Do
Own the collision avoidance safety case for humanoid robot platforms, from hazard identification through validation and field monitoring
Lead our humanoids’ Hazard Analysis and Risk Assessment, System-Theoretic Process Analysis (STPA), FMEA, and fault tree analysis for perception, planning, and actuation subsystems involved in collision detection and avoidance
Define and validate minimum safety distances, detection zones, and timing/spatial/force constraints for dynamic human-robot shared spaces, drawing on established frameworks (e.g., ISO 13855-style detection and approach speed logic) and adapting them where humanoid mobility and manipulation introduce new hazard geometries
Apply SOTIF (ISO 21448) methodology to identify and reduce risk from perception limitations, edge cases, and unknown-unsafe scenarios — not just component failures — and build this into a continuous scenario discovery and triage process
Define safety requirements for object/human detection, tracking, intent prediction, and fallback behaviors under sensor degradation or occlusion
Develop Functional Safety Concepts, Functional Safety Requirements, and Technical Safety Requirements for Collision Avoidance features
Derive requirements for fail-safe and fail-operational behaviors, degraded states, minimal risk maneuvers and human-robot interactions
Develop test cases for verification and validation of Collision Avoidance
Define, engineer, deploy, and employ system safety verification and validation equipment at HIL, SIL, and system level
Support incident investigation, near-miss analysis, and closed-loop safety requirement updates as fleet data accumulates
What We're Looking For
B.S. in Engineering with focus on optics, vision pipeline, and image processing
5+ years in safety engineering for robotics, autonomous vehicles, or other safety-critical human-interactive systems.
Working knowledge of functional safety standards and how to adapt them to novel domains (e.g., ISO 26262, ISO 13849, ISO 10218, ISO/TS 15066, IEC 61508, UL 4600)
Experience designing safety systems for complex electromechanical products with significant safety aspects
Experience in optics, machine vision, and computer vision, laser sensors, LiDAR, and time-of-flight and other cameras
Experience with safety analysis methods: STPA, FMEA, FTA
Comfortable with full stack - lens, sensor, ISP, compute processing, AI algorithms, behavior prediction and trajectory control
Evidence of hands-on engineering work — test benches, measurement, and root-cause analysis, not just documentation
Hands-on experience in verification and validation of safety requirements using HIL and SIL
Nice To Have (But Not Required)
Experience in humanoid robots, automotive, or autonomous mobile robots (AMR)
Experience in an autonomous driving engineering program, with hands-on ownership of SOTIF (ISO 21448) processes — scenario-based risk assessment, triggering condition analysis, and unknown-unsafe scenario reduction
Certified Functional Safety Engineer in Machinery Safety or Automotive/Autonomous Driving
Experience defining and validating safety-rated sensor fusion or redundant perception architectures
Exposure to simulation-based scenario generation and coverage argument tooling (e.g., scenario mining, adversarial scenario generation) from AV SOTIF work, applicable to humanoid edge-case discovery
In-depth understanding of safety-critical architectures for vision pipeline, compute, networking, and power distribution
Strong quantitative modeling skills (Python or MATLAB) for simulation, scenario analysis, and statistical validation of safety claims
Why This Role
Define the safety foundation for a humanoid robot operating in real-world human environments — work that is technically deep, consequential, and genuinely unsolved at this scale
Report directly to the Head of Safety and Certification with a clear path to grow into a leadership role as the safety organization scales alongside the company
Work at the intersection of functional safety, AI-driven control, and novel electromechanical systems — a combination that doesn't exist anywhere else