Engineering Manager, Prediction and Planning - Autonomous Vehicles

NVIDIA’s Autonomous Driving team is building the next generation of AI-based perception, prediction, and planning systems powering the world’s most sophisticated vehicles. We are seeking an Engineering Manager to lead our Prediction & Planning production organization, driving the delivery of robust, scalable, and safety-critical software into production. This role is ideal for a technical leader who thrives at the intersection of innovative autonomy algorithms and production execution — ensuring that innovative ideas transform into reliable, validated, and deployable driving intelligence.

What You’ll Be Doing:

• Lead end-to-end development of the Prediction and Planning stack, including motion prediction, behavior reasoning, trajectory generation, and decision-making.

• Develop and implement the production strategy for L2+/L2++ and beyond, ensuring timely delivery of outstanding software in line with NVIDIA’s advancements in autonomous vehicle technology.

• Establish robust workflows and metrics for software integration, SIL/HIL validation, scenario coverage, and regression testing in simulation and real-world environments.

• Partner with cross-functional teams — including Perception, Localization, Control, Simulation, and Infrastructure — to deliver tightly coordinated E2E autonomous driving solutions.

• Build and scale a high-performing global engineering team; mentor technical leads and strengthen interpersonal structure for sustained velocity.

• Guide resource planning, sprint execution, and program reviews to balance innovation, delivery speed, and stability.

• Represent Prediction & Planning in technical and product reviews, driving clarity and accountability across multi-site development.

What We Need To See:

• MS or PhD in Computer Science, Robotics, or related engineering field (or equivalent experience).

• 4+ years of experience leading a team with 8+ years of overall proven experience in software or robotics engineering, with 5+ years in autonomous driving or motion planning/prediction systems.

• Experience leading production software organizations that deliver sophisticated, multi-module systems to customers or partners.

• Deep understanding of path planning, motion prediction and intent modeling, Trajectory optimization or imitation/reinforcement learning for planning, Multi-agent reasoning or probabilistic decision-making for L2++/L3 autonomy.

• Proven record of delivering machine learning or planning systems into real-world or high-fidelity simulation environments.

• Strong proficiency in C++, Python, and GPU-based frameworks (PyTorch, TensorRT), and large-scale software development practices.

• Proven capacity in coordinating complex programs, outlining roadmaps, managing priorities across various teams, and supervising progress against stringent deadlines.

• Excellent communication and multi-functional leadership skills; comfortable working with engineering, product, and executive collaborators.

• Experience managing geographically distributed teams and establishing consistent engineering standards and delivery practices.

Ways To Stand Out From The Crowd:

• Successful track record of leading autonomous driving software releases or feature closure cycles from prototype to mass production.

• Experience with simulation-based validation, scenario management, and data-driven quality tracking frameworks.

• Deep knowledge of E2E AV software integration from perception through control, including dependencies, interface management, and performance tuning.

• Demonstrated ability to build, mentor, and scale technical leaders in a constantly evolving organization.

• Passion for delivering impact in autonomous driving technology.

NVIDIA is widely recognized as one of the world’s most innovative technology companies — driving breakthroughs in AI, autonomous systems, and high-performance computing. As part of our Autonomous Driving division, you’ll work alongside world-class engineers to bring next-generation driving intelligence from research to reality.