Senior Software Engineer, AV Planner - Autonomous Vehicles

Overview

• NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years.
• It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
• Today, we’re tapping into the unlimited potential of AI to define the next era of computing.
• An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world.
• Doing what’s never been done before takes vision, innovation, and the world’s best talent.
• As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.
• Come join the team and see how you can make a lasting impact on the world.
• We are looking for a Senior Software Engineer, AV Planner.
• As an AV Planning Engineer, you will work on state-of-the-art autonomous vehicle technologies with leaders in AI / deep learning, computer vision, mapping, prediction, and vehicle control.
• You will be responsible for developing, maintaining, and integrating behavior and motion planning algorithms and software for sophisticated urban driving.
• You should have strong analytical skills, good communication, and interpersonal capabilities to work in a team and make a joint effort towards a common goal.
• Prior knowledge of L4 autonomy, safety-critical systems, real-time software, and large-scale evaluation is highly valued.
• What you’ll be doing: Develop and ship behavior and trajectory planning for an L4 robotaxi (lane changes, merges, intersections, unprotected turns, yielding, stop-and-go, curbside operations).
• Design planning technologies needed to build the AV software stack; write new software modules from scratch that drive vehicles safely and comfortably in dense urban environments.
• Build optimization-, sampling-, and/or search-based planning approaches with vehicle dynamics and constraints (collision avoidance, comfort/jerk limits, road-rule compliance).
• Define and implement fallback and degraded-mode behaviors (e.g., safe stop / minimal risk maneuvers) and contribute to safety-oriented design (failure modes, redundancy, validation evidence).
• Integrate planning with prediction, perception, mapping/localization, and controls; define clean interfaces and troubleshoot end-to-end system issues using logs and scenario replay.
• Build and improve offline and closed-loop simulation benchmarks and metrics for planning quality (safety, legality, comfort, progress), and drive regression prevention.
• Define and build tools to accelerate debugging, scenario triage/mining, evaluation automation, and parameter/config management across vehicle platforms.
• Drive integration efforts across different platforms/vehicle types; support on-vehicle issue reproduction and resolution.
• Most importantly, work on groundbreaking and innovative technology, tackle difficult problems, and help build a world-class system! What we need to see: BS, MS, or higher degree in Computer Science, Electrical Engineering, Robotics, Mechanical Engineering, or equivalent experience.
• 5+ years of experience in the relevant field.
• Strong software engineering skills in C/C++ (production-quality, performance-aware, testable code); Python experience for tooling/evaluation is a plus.
• Knowledge and hands-on background in several of the following: motion planning, decision-making, optimization, search, sampling-based planning, geometry, vehicle dynamics/kinematics, real-time systems.
• Experience building and using simulation and evaluation pipelines, writing unit/integration tests, and preventing regressions via automation.
• Strong debugging skills across multi-module systems; ability to turn ambiguous on-road/sim failures into actionable fixes.
• Ability to communicate clearly and collaborate effectively across functions (prediction/perception/controls/safety).
• Ways to stand out from the crowd: Hands-on experience shipping urban/L4 robotaxi planning (behavior + trajectory) with measurable improvements in safety and ride quality.
• Experience with interaction-aware or uncertainty-aware planning (risk-sensitive decision making, robust constraints, prediction coupling).
• Experience with automotive safety concepts and analysis methods (e.g., FMEA) and building credible validation strategies.
• Track record of leading architecture/roadmap and mentoring, or rapidly delivering high-quality features with strong engineering fundamentals.
• PhD with relevant experience or significant industry experience in autonomy/robotics.
• Academic and commercial groups around the world are powering a revolution in artificial intelligence using deep learning techniques running on NVIDIA GPUs, enabling breakthroughs in problems from image classification to speech recognition to natural language processing.
• Intelligent machines powered by AI computers that can learn, reason and interact with people are no longer science fiction.
• Today, a self-driving car powered by AI can navigate complex environments and make safe decisions in real time.
• This is truly an extraordinary time.
• The era of AI has begun.