10 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Develop, maintain, and integrate autonomous vehicle control algorithms and software.
- Develop vehicle trajectory tracking, model predictive control, state estimation, vehicle dynamics, and control functionality for applications such as adaptive cruise control and lane keeping.
- Design autonomous vehicle software-stack technologies and write new real-time software modules in C/C++.
- Contribute to system architecture, failure-mode analysis, redundancy, and product-level design decisions.
- Build offline and online performance benchmarks for vehicle control.
- Define and build vehicle-dynamics tuning tools and manage calibration updates across vehicle types.
- Drive integration across platforms and troubleshoot vehicle control and actuation issues.
- Develop and maintain vehicle test suites and automated unit and system-level tests to identify integration issues and prevent regressions.
Requirements
- BS, MS, or higher degree in Mechanical Engineering, Electrical Engineering, Computer Science, or equivalent experience.
- 8+ years of relevant work experience.
- Hands-on control-theory experience in at least three areas, including classical, modern, nonlinear, model predictive, optimal, robust, or sliding-mode control.
- Knowledge of state-estimation techniques such as Luenberger observers and Kalman filters.
- Ability to develop vehicle models, perform parameter identification, and conduct benchmarking.
- Experience designing and prototyping high-level algorithms in MATLAB, Simulink, or Python and implementing them in C/C++.
- Experience with architectural design and software development for real-time embedded control systems such as vehicle ECUs.
- Understanding of automotive software test and verification methodologies, including unit- and system-level testing.
- Experience integrating, tuning, and validating control software with application, driver, and vehicle-network layers.
- Experience developing or using in-vehicle control-software verification and calibration tools for autonomous vehicle applications.
- Preferred qualifications include autonomous-vehicle or ADAS experience, automotive safety and FMEA knowledge, safety-critical control-system product experience, deep learning and neural-network knowledge, 12+ years of automotive or autonomous-driving engineering experience, or a relevant PhD.
Benefits
- Eligible for equity and benefits.
- Base salary is determined by location, experience, and other objective job-related factors; the posting lists Level 4 and Level 5 salary ranges.
- Applications accepted at least until November 3, 2026.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.