Principal Engineer Team Lead, AV Behavior

Motional•Pittsburgh, PA

3d•$200,000 - $275,000•Hybrid

About The Position

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year. We are looking for a passionate, self starting engineering leader to lead the AV Behavior Understanding and Evaluation team within the SRP organization. This team defines the standards for safe, comfortable, and assertive autonomous driving. We bridge the gap between systems engineering and real-world performance by decomposing the Operational Design Domain (ODD) into actionable competencies. The team owns the behavior definition, actionable driving policies backed by tests, and acceptance criteria derived from standards and human benchmarks. The team works closely with the autonomy teams on both target setting and validation. We are seeking a hands-on Principal Engineer Team Lead to drive the design, evaluation, and scaling of these systems through data-driven design backed by structured and large scale assessment in simulation and on the road. You will lead a high-performing team to transform complex data into measurable progress toward a safer, smarter transportation future.

Requirements

Bachelor's degree and 7+ years of experience in Systems Engineering, Autonomous Systems, or Robotics, with deep expertise in one and working knowledge of the others.
Or Master’s degree/PhD and 5+ years of experience
3+ years of experience leading and scaling data-driven evaluation programs for autonomous driving or safety-critical emerging technologies.
A hands-on technical leader with a proven track record of growing small, high-performing teams.
Demonstrated track record in decomposing ODD requirements into vehicle capabilities, driving behavior logic, and defining measurable acceptance criteria.
Expert at leveraging large-scale simulation, track, and road data to extract actionable technical insights that drive resolution with development teams.
Proven track record of building consensus and driving alignment across multidisciplinary teams—spanning Autonomy, Infrastructure, and Operations—by leveraging technical influence over organizational authority.
Strong foundation in statistical methodology, Data Science, and scientific rigor.
Proficiency in Python, SQL, and data visualization techniques.
Excellent communication skills; capable of articulating complex concepts to technical peers and executive leadership alike.
Self-starter with a proactive mindset for driving ambiguous projects to completion.

Nice To Haves

Master’s degree in Systems Engineering, Autonomous Systems, or Robotics
Familiarity with SOTIF, ISO 26262, UL4600, AVSC Behavior competencies and other industry standards
Experience shaping product roadmaps
Experience establishing and leveraging industry benchmarks as well as human naturalistic driving behaviors to improve autonomous driving
Familiarity with Reinforcement Learning (RL)
Experience collaborating within agile environments and global, distributed teams.
Experience with Industry standards and establishing human benchmarks
Specialized expertise in creating expansive datasets
Experience collaborating in an agile development environment

Responsibilities

Design the System Behavior: Decompose ODD requirements into system and subsystem behaviors and interfaces to ensure vehicle capabilities meet product requirements. Characterize the performance target against parameters used to define AV capabilities to provide nuance in performance evaluation
Develop actionable policies and measurable targets: Convert legal and industry policy narratives to mathematical and/or specific requirements that the autonomy teams can implement. Leverage human benchmark and industry standards to establish measurable acceptance criteria for system readiness
Drive Evaluation Strategy: Advance our performance assessment framework by defining key metrics and reward functions. Derive Launch Criteria and Driving policy and strategically plan and execute testing campaigns leveraging advanced structured and large scale simulation, closed-course tracks, and on-road data.
Lead and Scale: Mentor and grow a high-performing engineering team. Foster a culture of technical excellence, scientific rigor, and data-driven decision-making.
Cross-Functional Collaboration: Partner with Autonomy, Infrastructure, and the other Systems teams to drive design improvements. Ensure features generate a net positive effect on system safety, comfort, and assertiveness and meet our launch criteria
Data exploration: Leverage data science techniques and existing infrastructure to understand the problem space and engage with development teams to drive resolution in close collaboration with System Performance
Incorporate Bleeding Edge technology: Leverage a combination of learning methods and metrics along with classical metrics to stretch the horizon of performance evaluation