Senior Manager - AV Evaluation

Job description

Job responsibilities

• Own the strategy, roadmap, and operating plan for a distinct Autonomy Evaluation business area spanning methodology , platforms, and infrastructure ensuring alignment with autonomy product goals, safety priorities, and…
• Define and evolve the end-to-end evaluation strategy for autonomy performance, including scenario coverage, behavioral quality measurement, trend detection, risk assessment, and release-gating readiness.
• Drive cross-functional alignment with Autonomy, Simulation, Systems, and Safety organizations to translate ambiguous validation needs into clear priorities, roadmaps, and execution plans.
• Oversee evaluation approaches for ML components across perception , prediction, and planning, ensuring methods are explainable, scalable, and useful to development and verification teams.
• Guide the team in developing new statistical and machine learning methods to quantify performance and identify behavior patterns across scenes and operational domains.
• Help the organization leverage emerging AI techniques, including VLMs and LLMs where appropriate, to classify autonomy performance and prioritize validation work with human-in-the-loop review.
• Maintain a high technical bar through strong system design, code review, testing, observability, and engineering best practices .
• Drive the development of scalable evaluation infrastructure, including data pipelines, workflow orchestration, developer tooling, and service interfaces that improve reliability and iteration speed.

Job requirements

• 10+ years of relevant experience in robotics, autonomous systems software, data analysis, ML evaluation, autonomy analytics , or large-scale data/infrastructure platforms with a track record of delivering complex…
• 5+ years of people leadership experience in complex engineering organizations, including leading managers or senior technical leaders.
• Demonstrated ownership of a distinct technical or business area, including strategy, roadmap, execution planning, KPI management, and cross-functional outcomes.
• Demonstrated technical leadership, including driving architectural decisions, influencing cross-team designs, and owning complex services or platforms end-to-end.
• Experience building or leading production infrastructure for large-scale data processing, workflow orchestration, observability, and service reliability.
• Experience developing Python/C++ in production team environments, including testing, performance, and code review.
• Experience evaluating dynamic systems using numerical, statistical, and/or machine learning methods, including time-series data, state derivatives, dynamics, and interconnected subsystems.
• Strong analytical curiosity and a disciplined approach to root-causing anomalous data and system discrepancies.