2 days ago
Santa Clara, CA, USASenior / Staff+
H1B sponsor
Base Salary
$152k - $288k/yr
Responsibilities
- Integrate learned driving models with vehicle interfaces, sensor inputs, localization, mapping, safety systems, and autonomous-driving components.
- Define model input, output, timing, state-management, and runtime interface contracts.
- Partner with model developers to improve model quality, debuggability, runtime behavior, and deployment readiness.
- Investigate differences between model behavior in development environments and on target vehicle platforms.
- Optimize model inference and supporting software for latency, throughput, memory, determinism, and power requirements.
- Develop tools and metrics for driving quality, safety, robustness, and regression evaluation at scale.
- Perform in-vehicle testing, collect and analyze driving data, and complete autonomous-driving missions.
- Develop production software in C++ and Python using CUDA and other GPU-accelerated technologies.
Requirements
- PhD with at least 1 year, MS with at least 3 years, or BS or equivalent experience with at least 5 years of relevant experience in computer science, computer engineering, robotics, machine learning, or a related field.
- Strong C++ programming, software architecture, debugging, and performance-analysis skills, with experience in CUDA and TensorRT model-inference technologies.
- Proficiency in Python and experience with machine-learning frameworks such as PyTorch.
- Experience developing software on Linux and embedded or real-time operating systems such as QNX.
- Experience integrating machine-learning models into complex, performance-sensitive production systems.
- Ability to diagnose issues across model behavior, application software, middleware, operating systems, and hardware.
- Experience with autonomous driving, robotics, ADAS, or another real-time intelligent system.
- Preferred qualifications include experience deploying end-to-end driving, robotics, or embodied-AI models on production hardware; model optimization, quantization, compilation, profiling, and hardware-aware neural-network design; and turning research models into robust, measurable, maintainable product functionality.
Benefits
- Eligible for equity and benefits.
- Base salary is determined by location, experience, and pay for similar positions; applications will be accepted at least until September 22, 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.