Staff System Engineer - ADAS/AD Safety
- Collaborate with the Function Safety team to jointly review and align on HARA, Safety Goals (SG), for ADAS and AD features.
- Own the derivation and authoring of Technical Safety Concepts and Technical Safety Requirements, ensuring proper allocation to sensors, ECUs, software modules, actuators, vehicle networks, and operational assets.
- Integrate SOTIF thinking into the safety case: performance limitations, triggering conditions, misuse and edge-case scenarios, especially for perception and AI/ML components.
- Define and own the end-to-end safety case framework for ADAS/AD stack (structure, claims, argumentation style, and evidence model).
- Identify top-level safety objectives and transform them into safety case claims, sub-claims, and required evidence (e.g., using GSN or equivalent notations).
- Act as the technical focal point for safety case topics in design reviews, release gates, and change control boards.
- Contribute to building a Safety Management System (SMS) and safety governance structures over time (e.g., safety board, safety metrics).
- Bachelors in System Engineering, Electrical Engineering, Computer Science
- 8+ years of related experience in system safety, functional safety, or safety assurance for autonomous systems, ADAS, robotics, or similar safety-critical domains.
- Demonstrated experience with at least one full safety lifecycle (concept through SOP/launch) for a complex system.
- Hands-on experience with safety case development or maintenance, including structuring claims, arguments, and evidence
- Solid working knowledge of ISO 26262, ISO 21448 (SOTIF) and UL 4600
- Practical experience with safety analysis methods (e.g., HARA, FMEA, FTA, STPA) and their integration into a traceable safety argument.
- Strong written communication skills; able to author clear safety concepts, analyses, and safety case documentation targeted at both engineers and leadership.
- Strong systems thinking: comfortable reasoning from high-level societal/operational risk down to implementation details.
- High ownership bias: willing to create structure where none exists and drive alignment across teams.
- Ability to influence without authority and bring engineers, PMs, and leaders along on safety decisions.
- Clear, concise communication; able to explain complex safety trade-offs to both technical and non-technical audiences.
- Master’s degree in system engineering, Electrical Engineering, Computer Science experience
- 6 years related experience or a PhD with 3 years experience
- Experience with automated driving or advanced ADAS (multi-sensor stacks: camera, radar, lidar, ultrasonic, GNSS/IMU, HD maps).
- Demonstrated ownership of a UL 4600-aligned safety case or similar safety case for autonomy.
- Working knowledge of ISO-8800
- Familiarity with AI/ML safety topics (data pipeline safety, performance monitoring, ODD/OSD concepts, SOTIF for perception/behavior).
- Experience working in or with fast-moving startups or new product lines, balancing rigor with pragmatism.
- Exposure to regulatory interactions, external audits, or certification bodies on safety topics.
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