Technical Program Manager, Evaluation & Validation

Overview

In this Technical Program Manager role, you will coordinate cross-team efforts across simulation, evaluation, and validation to ensure the AI Driver is ready for road deployment. You’ll align platforms, datasets, and validation workflows with release criteria, balancing speed with safety. Your leadership will connect technical delivery to measurable outcomes like developer velocity and validation credibility, while working with Autonomy, Science, Release, Product, and Safety. This position offers the chance to shape safety-critical AI in a fast-moving, competitive space and drive confidence in on-road releases.

Pay / Benefits

• competitive equity package
• hybrid work arrangement (Sunnyvale, CA)
• inclusive interview experience
• disability accommodations on request
• salary range provided
• career growth opportunities

Responsibilities

• Own end-to-end delivery of cross-team programs spanning simulation, evaluation, and validation
• Plan and sequence roadmaps across simulators, datasets, evaluation, and triage; manage dependencies, risks, and trade-offs
• Tie platform delivery to outcomes such as developer velocity, signal quality, and time-to-insight
• Coordinate release-gating validation with Autonomy, Science, Release, Product, and Safety
• Lead planning, reviews, and retros to communicate progress and risk to engineers, partners, and senior leadership
• Champion continuous improvement of tooling, processes, and ways of working across platforms

Key requirements

• Bias for action: 8+ years leading complex, multi-team programs
• Technically strong: able to converse with engineers and scientists on simulation, evaluation, ML, and validation
• Stays neutral and adapts under pressure in safety-critical environments
• Strong project management: planning, prioritising, risk and dependency management
• Clear communicator & collaborator across multiple teams
• Data-driven: using metrics to steer delivery and decisions
• Growth mindset: openness to feedback and improvement
• Systems thinking: understanding how changes ripple through a system
• Product-minded: focus on outcomes and defining what good looks like

• clear communicator
• collaborator
• data-driven decision making
• simulation
• evaluation
• ML

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