Staff Planner Sw Quality Architect

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech. With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: will...
Lead the SW Quality of our Planner Architecture, focusing on building robust fault-tolerance systems to resolve critical downstream/upstream performance bottlenecks and ensure continuous, safe vehicle operation.Act as a critical technical bridge and enabler between the Motion Planning and the Onboard SW Teams, driving overall SW quality improvement and reliability.Design and develop motion planning software and algorithms, building the brain which orchestrates decision making in dynamic, uncertain and interactive traffic scenarios.Be part of a team of multidisciplinary Engineers and Research Scientists using an AI-first approach to enable safe self-driving at scale.Manage the experimentation pipeline for research and data generation.Qualifications:
MS/PhD or Bachelor degree with a minimum of 6 years of industry experience in Computer Science, Robotics and/or similar technical field(s) of study.Experience owning software on a shipped product with reliability requirements.Strong grasp of software engineering principles (i.E. code review, unit testing, scalability, maintainability, SW architecture, full lifecycle).Experience in planning/decision making approaches (e.G., optimal control, optimization based approaches, search methods, probabilistic decision making).Production-quality coding skill in Python or C++.Open-minded and collaborative team player with the willingness to help others.Able to maintain progress towards long-term goals while working on short-term problems.Passionate about self-driving technologies, solving hard problems, and creating innovative solutions.
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