Principal Robotics Functional Safety Engineer (AI/ML)

Principal Functional Safety Engineer, AI/ML & Robotics

Location: Hybrid, Fremont, CA or Remote in the United States

About the Role

Our client is seeking a Principal Functional Safety Engineer focused on AI/ML-enabled robotic systems to help define how safety is engineered for increasingly intelligent and autonomous machines operating alongside people.

This is a senior technical leadership role at the intersection of functional safety, AI/ML, perception, autonomy, controls, and robotics. You will help establish safety architectures and assurance strategies for systems whose behavior cannot always be addressed through traditional deterministic functional safety approaches alone.

The ideal candidate brings a strong foundation in functional safety and risk engineering, but also understands the emerging challenges associated with AI/ML-enabled safety functions, perception uncertainty, probabilistic behavior, SOTIF, and runtime safety constraints.

You will work closely with functional safety, AI/ML, perception, autonomy, controls, embedded software, hardware, and systems engineering teams to ensure intelligent robotic functionality operates within clearly defined and validated safety boundaries.

What You’ll Work On

• Lead functional safety strategy for AI/ML-enabled robotic features, from concept and architecture through verification, validation, and deployment.
• Develop safety approaches for perception, autonomy, machine learning, and other non-deterministic or probabilistic functionality.
• Define how AI/ML components interact with traditional safety architectures, including safety monitors, fallback behaviors, fault responses, runtime constraints, and safe-state logic.
• Apply and evolve methodologies related to SOTIF, ISO 21448, ISO/IEC TS 22440, and ISO/IEC TS 25223, particularly around AI behavior and uncertainty.
• Evaluate hazards associated with ML model limitations, perception failures, environmental uncertainty, edge cases, and unintended system behavior.
• Define safety requirements and acceptance criteria for AI/ML-enabled functionality and translate them into actionable requirements for ML, perception, controls, software, and systems teams.
• Help establish methods for demonstrating that AI/ML-enabled behaviors remain within defined safety envelopes and operational boundaries.
• Lead architecture-level safety decisions that balance system performance, technical risk, uncertainty, and compliance.
• Create and maintain functional safety deliverables including risk assessments, safety requirement specifications, safety concepts, FMEDA, SISTEMA analyses, validation plans, and safety cases.
• Apply established functional safety frameworks including ISO 13849, IEC 62061, IEC 61508, ANSI/RIA R15.08, and ISO 10218 where applicable.
• Partner with V&V teams to develop testing strategies for safety-critical AI/ML functionality, including edge cases, abnormal conditions, uncertainty, degraded performance, and failure scenarios.
• Collaborate across AI/ML, perception, controls, software, hardware, systems, and safety teams to integrate safety throughout the development lifecycle.
• Monitor the rapidly evolving regulatory and standards landscape surrounding AI safety, autonomous systems, and intelligent robotics.
• Help shape organization-wide functional safety strategy and mentor other engineers in both traditional and emerging AI/ML safety practices.

What We’re Looking For

• BS, MS, or PhD in Robotics, Computer Science, Electrical Engineering, Mechatronics, Systems Engineering, or a related technical field.
• Significant experience in functional safety, safety-critical systems, robotics, autonomous systems, or intelligent machines.
• Deep understanding of functional safety lifecycle practices and frameworks such as IEC 61508, ISO 13849, IEC 62061, or comparable standards.
• Experience developing safety concepts and architectures for complex systems involving software, sensing, controls, perception, or autonomy.
• Strong understanding of traditional hazard analysis and risk reduction methods, including the hierarchy of controls.
• Ability to define safety requirements and work with engineering teams to implement, verify, and validate them.
• Experience with safety analysis methods and tools such as FMEA/FMEDA, FTA, HARA or equivalent risk-assessment methodologies, and SISTEMA.
• Ability to communicate complex safety concepts across AI/ML, software, controls, systems, hardware, product, and leadership teams.

Particularly Strong Fit

We’re especially interested in candidates with experience in one or more of the following:

• Functional safety of AI/ML-enabled systems
• SOTIF / ISO 21448
• ISO/IEC TS 22440 and emerging AI functional safety practices
• ISO/IEC TS 25223 and uncertainty quantification for AI systems
• Safety of perception systems, including camera, lidar, radar, or multi-sensor systems
• Safety architectures for autonomous vehicles, ADAS, robotics, industrial automation, or other autonomous machines
• Managing perception uncertainty, model limitations, edge cases, and non-deterministic behavior
• Runtime monitoring, safety envelopes, fault containment, fallback strategies, and safe-state design
• Verification and validation of ML-based or probabilistic systems
• Safety-critical embedded software or firmware
• TÜV Functional Safety Engineer certification or equivalent
• Standards development or participation in industry safety working groups

Work authorization: Candidates must currently be authorized to work in the United States.