ML Prediction and Planner – Tech Lead @ Applied Intuition

About Applied Intuition Applied Intuition is the vehicle intelligence company that accelerates the global adoption of safe, AI-driven machines. Founded in 2017, Applied Intuition delivers the toolchain, Vehicle OS, and autonomy stacks to help customers build intelligent vehicles and shorten time to market. Eighteen of the top 20 global automakers and major programs across the Department of Defense trust Applied Intuition's solutions to deliver vehicle intelligence. Applied Intuition services the automotive, defense, trucking, construction, mining, and agriculture industries and is headquartered in Mountain View, CA, with offices in Washington, D.C., San Diego, CA, Ft. Walton Beach, FL, Ann Arbor, MI, London, Stuttgart, Munich, Stockholm, Seoul, and Tokyo. Learn more at appliedintuition.com. We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments. (Note: For EpiSci job openings, fully remote work will be considered by exception.)About the role We are looking for a lead software engineer with expertise in ML-first prediction and planning for autonomous vehicles or mobile robots. You will lead the engineering team in prototyping, evaluating, refining, and deploying state-of-the-art ML capabilities for our autonomous vehicle stack. At Applied Intuition, you will: Lead the development of machine learning models for joint behavior prediction and planning, with the goal of end-to-end differentiable autonomy Architect integrated ML systems that reason over latent scene representations from perception to directly inform or generate trajectory decisions Implement data-driven approaches that optimize the full autonomy stack jointly Collaborate tightly with Perception, Mapping, and Simulation teams to design shared representations…

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