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.
You will also be eligible for equity and benefits.
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
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