Define and build tools to tune our vehicle dynamics control and manage calibration updates for various vehicle types.
Drive integration efforts of control functionality across different platforms, support troubleshooting of control and actuation issues in vehicles.
Develop and maintain vehicle test suites to detect control integration problems, develop and maintain automated tests to ensure SW quality and prevent regressions.
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 Mechanical Engineering, Electrical Engineering, Computer Science or equivalent experience
8+ years of work experience in relevant fields
Knowledge and hands-on application background in control theories, including at least three of the following fields: classical control, modern control, nonlinear control, MPC, optimal control, robust control, sliding mode control.
Understanding of state estimation techniques such as Luenberger observer, kalman filter, etc.
Ability to develop vehicle models and perform parameter identification and benchmarking.
Knowledge of high-level algorithm design and prototyping in simulation environments (Matlab/Simulink/Python) to product oriented implementation with C/C++.
Experience in architectural design and software development with C/C++ for real-time embedded control systems, such as vehicle ECU systems.
Understanding of test and verification methodologies for automotive software, know-how in writing unit and system level tests.
Experience of integrating, tuning, and validating prototype and/or production control software with application, driver, and vehicle network layers.
Experience of development and/or usage of in-vehicle control software verification and calibration tools for autonomous vehicle applications.
Ways to stand out from the crowd
Hands-on experience in autonomous vehicle or advanced driver assist system development such as lane keeping, adaptive cruise control, etc.
Background in automotive safety concept, failure mode, common analysis tools such as FMEA
Experience in developing and launching vehicle safety critical control system products such as powertrain, steering system, brake system, advanced driver assist system, etc.
Understanding of deep learning and neural network concepts
12+ years engineering experience at automotive OEM, tier-1 supplier or autonomous driving start-ups
PhD with relevant experience
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 meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. This is truly an extraordinary time. The era of AI has begun.
- Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
- 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
