Lead Product Manager, Autonomy
@ WaabiLead Product Manager, Autonomy
This job is still taking applications, but it's been up a while.
About the job
Waabi, led by AI expert Raquel Urtasun, develops physical AI for autonomous trucks and robotaxis. Located in Toronto, SF, Dallas, Pittsburgh, they aim to transform transportation through innovative tech and diverse teams.
Requirements
- 8+ years in Product Management
- Experience with autonomous vehicles
- Strong analytical skills
- Excellent communication abilities
- Leadership in high-growth environments
Qualifications
- Proven results in complex AI systems
- Cross-functional team coordination
- Safety-critical software understanding
- Passion for autonomous tech
- Deep industry knowledge
Full job description
We are seeking a Lead Product Manager to lead the strategy and execution of the core autonomy stack that powers the Waabi Driver. This role is central to the success of the business and requires a leader who can bridge the gap between cutting-edge AI research and real-world commercial requirements. You will provide focused ownership and coordination across teams, ensuring that autonomy efforts are aligned with both technical milestones and driverless launch objectives. You will bring the strategic depth and execution rigor needed to manage complexity at this scale, turning advanced autonomy capabilities into a reliable, commercial product.
You Will...
- Define, develop and execute the Autonomy roadmap, aligning core driving capabilities with the company’s driverless and commercial milestones across both the trucking and robotaxi verticals.
- Drive the end-to-end product lifecycle for autonomy features by translating complex use cases into actionable requirements and establishing performance benchmarks for deploying core driving behaviors in the real world.
- Lead cross-functional alignment across Engineering, Design, Research, Simulation, Systems Engineering, Safety, and Commercial teams to define product requirements, manage technical trade-offs, and develop frameworks that make autonomy performance measurable and transparent.
- Analyze performance data and feedback from simulation, track, and road testing to develop a comprehensive understanding of system readiness metrics and systematically prioritize issue resolution.
- Be a team player who prioritizes trust, transparency, and honesty, leading by example in a high-stakes, safety-critical environment.
- Monitor key performance indicators (KPIs) such as ODD coverage, system readiness, and route viability to make data-driven decisions that accelerate commercialization.
Qualifications:
- Minimum of 8+ years of experience in a Product Management role, with a proven track record in autonomous vehicles, robotics, or complex AI/ML systems.
- Strong analytical and problem-solving skills to resolve dependencies, inform strategic decisions, and evaluate tradeoffs between performance and safety.
- Excellent communication and interpersonal skills, with significant experience drafting written strategy documents and slides to communicate complex autonomy concepts to diverse stakeholders.
- Demonstrated leadership abilities, with experience driving results and cross-functional alignment in fast-paced, high-growth environments.
- Exhibits exceptional empathy, fostering a deep understanding of the needs of internal engineering teams, safety drivers, and commercial partners.
- Adaptable and versatile, proficient at navigating the shift from R&D-heavy environments to product-driven commercial execution.
- Able to maintain progress towards long-term architectural goals while solving immediate operational hurdles.
- Passion for autonomous systems, safety-critical software, and building the "brain" of the vehicle that will redefine the future of freight.
Bonus:
- Deep understanding of the autonomy stack (e.g. Perception, Prediction, Motion Planning, Localization) and the nuances of autonomous driving operations.
- Experience defining operational boundaries and safety validation milestones to drive the successful deployment of autonomous features in complex environments.
- Technical experience in autonomous vehicle development or a background in Computer Science/Robotics.
- Experience working in an Agile/Scrum environment tailored for deep-tech research.
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