Technical Program Manager, Evaluation & Validation
$214.9k - $274kFull-time
Wayve
About Us Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The role As a Technical Program Manager in Simulation, Evaluation & Validation at Wayve, you'll drive delivery across the platforms and processes that prove the AI Driver is ready for the road - open and closed-loop simulation, the evaluation platform, synthetic data, critical-event pipelines, and behaviour validation. Your programs gate real on-road releases, so your impact is measured in release confidence, signal quality, and developer velocity. Working with engineers and scientists across Autonomy, Science, Release, Product, and Safety, you'll bring structure to a complex, cross-cutting, safety-critical space in a fast-moving environment. A successful TPM is a force multiplier - helping teams move faster, more effectively, and with purpose. Key Responsibilities
- Drive program delivery: Own end-to-end delivery of cross-team programs spanning simulation, evaluation, and validation.
- Sequence cross-cutting initiatives: Compose roadmaps across simulators, datasets, evaluation, and triage; manage dependencies, risks, and trade-offs, and escalate early with clear options.
- Tie work to outcomes: Connect platform delivery to measurable outcomes - developer velocity, signal quality, cost per evaluation, time-to-insight, and validation credibility.
- Coordinate release-gating validation: Partner with Autonomy, Science, Release, Product, and Safety on acceptance criteria and the validation that gates releases.
- Run delivery rhythms: Run planning, reviews, and retros, and communicate progress and risk to engineers, partners, and senior leaders.
- Champion continuous improvement: Improve tooling, processes, and ways of working across the platforms.
- Bias for action: 8+ years leading complex, multi-team programs (or a strong record at this level). You lead high-complexity work across teams and get things done.
- Technically strong: Credible with engineers and scientists across simulation, evaluation, ML, and validation; you reason about how data, simulator fidelity, and metric design propagate into release confidence, even though you won't write production code.
- Stays neutral and adapts under pressure: Effective in ambiguous, safety-critical environments; you flex your style and bring structure without slowing delivery.
- Strong project management: Skilled at planning, prioritising, and managing risk and dependencies across teams.
- Clear communicator & collaborator: You influence without authority across Autonomy, Science, Release, Product, and Safety.
- Data-driven: Comfortable defining and using metrics - signal quality, coverage, time-to-insight - to steer delivery and decisions.
- Growth mindset: Open to feedback and always looking to improve.
- Systems thinking: You reason about how the parts of a complex system fit together, and how a change in one area ripples into others.
- Product-minded: You focus on outcomes and the people your programs serve - prioritizing by impact and defining what good looks like, not just tracking activity.
- Experience in autonomous vehicles, robotics, or another safety-critical AI/ML program.
- Familiarity with simulation, synthetic data, evaluation harnesses, or ML observability tooling at production scale.
- Working knowledge of SOTIF (ISO 21448), ISO 26262, or other safety standards relevant to validating learned systems.
- An engineering or computer science degree, or experience working as an engineer; excels in Jira (or similar).
Vacancy posted 2 days ago
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