Staff Systems Engineer - Safety Methodologies

Waabi is a technology startup building technologies to transform the way the world moves through autonomous transportation. The Staff Systems Engineer will develop and implement safety framework methods for driverless autonomy readiness decisions, using simulation, real-world data, and generative AI techniques. The role will lead safety testing, evaluation pipelines, traceable safety artifacts, and cross-functional technical collaboration.

Responsibilities:

• Inform driverless release testing by developing sample-efficient, high-signal safety datasets across simulation and closed-course track testing
• Establish and manage a robust feedback loop from on-road monitoring and safety relevant events to continuously expand and refine test coverage
• Validate and optimize safety evaluation pipelines by conducting comparative analyses on core safety frameworks and benchmark criteria to continuously evolve our safety frameworks
• Own the creation of clear and structured safety artifacts, ensuring all readiness decisions are transparent and fully traceable to validation evidence
• Mentor peers by fostering a culture of technical excellence and driving clear, constructive collaboration between teams

Requirements:

• Undergrad required
• 7+ years of automotive, robotics or closely related industry experience
• Experience with using simulation and real-world testing to make readiness decisions
• Excellent scripting and data analysis skills (Python, SQL), and a solid foundation in statistics
• Experience with building a strong safety case for autonomous vehicles
• Ability to communicate complex concepts or data in a simple-yet-accurate manner
• Collaborative team player who works effectively across functional boundaries, driving evidence-backed decisions
• Passionate about autonomy, solving hard problems, and creating innovative solutions
• Masters or PhD within an engineering discipline preferred
• Experience in launching a driverless product
• Experience implementing software systems components
• Experience building software systems from scratch
• Experience in machine learning
• Proficiency with data mining and advanced statistical analysis