Senior Software Engineer - Autonomous Driving

NVIDIA; Santa Clara (CA); On-site; USD 224,000 - 356,500; Full time

Benefits offered by this job

Equity options

Inclusive work environment

Health benefits

Job summary

NVIDIA is seeking a Senior Software Engineer to lead innovations in automotive platform performance at their Santa Clara location. This role involves optimizing and deploying deep neural networks for autonomous driving applications, focusing on performance and safety.

Ideal candidates should have 12+ years of experience in AI/ML, strong skills in C/C++, and a deep understanding of related frameworks like TensorRT. The base salary range is $224,000 to $356,500, and benefits include equity options.

Qualifications

• 12+ years of software engineering experience.
• Strong experience in systems software and AI/ML.
• Experience optimizing DNN models.

Responsibilities

• Lead architecture and technical strategy for inference workloads.
• Drive performance analysis across DNN models.
• Develop model optimization techniques.

Skills

C/C++

Python

AI/ML infrastructure

Deep learning inference

TensorRT

Education

BS, MS, or PhD in relevant field

Tools

CUDA

ONNX

PyTorch

Job description

Our Automotive Platform Team is building the software foundation for scalable, high-performance vehicle computing platforms that power autonomous driving, ADAS, digital cockpit, and centralized vehicle architectures. We are looking for exceptional engineers who thrive on solving deeply complex system-level challenges and shaping the future of automotive computing.

We are seeking a Senior Software Engineer for next-generation innovations in automotive platform performance, AI model optimization, scalability, and system architecture! In this highly visible technical leadership role, you will drive architecture, optimization, and execution across the autonomous driving software stack, with a focus on optimizing and deployment of deep neural networks that are fast, efficient, reliable, and deployable on NVIDIA automotive compute platforms. You will work at the intersection of core platform, deep learning inference, TensorRT and related compiler/runtime technologies, CUDA/GPU performance, model compression, platform software, and safety-aware automotive deployment.

What you'll be doing:

• Lead architecture and technical strategy for optimizing inference workloads in autonomous driving applications.
• Drive end-to-end performance analysis across DNN models, TensorRT/compiler flows, CUDA kernels, memory behavior, scheduling, runtime services, and automotive platform constraints.
• Develop and guide model optimization techniques such as quantization, pruning, distillation, graph optimization, operator fusion, kernel selection, and layout/memory optimization.
• Collaborate with TensorRT, CUDA, compiler, silicon architecture, perception, planning, DriveOS and safety platform teams.
• Build tools, methodologies, and metrics for profiling, benchmarking, debugging, and validating model and platform performance.

What we need to see:

• BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
• 12+ years of software engineering experience in systems software, AI/ML infrastructure, deep learning inference, compiler/runtime technology, or platform performance.
• Strong C/C++ and practical Python experience.
• Deep familiarity with TensorRT, TensorRT-LLM, ONNX, PyTorch, CUDA, Triton, or related frameworks.
• Experience optimizing DNN models for latency, throughput, memory footprint, and power.

Ways to stand out from the crowd:

• Hands-on experience with TensorRT internals, CUDA kernels, Triton kernels, or other compiler/runtime technologies.
• Experience deploying optimized DNNs, LLMs, VLMs, or perception models on embedded, edge, robotics, or automotive platforms.
• Background in autonomous driving, ADAS, robotics, real-time systems, safety-aware software, or deterministic low-latency systems.
• Experience with ISO 26262, QNX, Safe RTOS, DriveOS, Linux, hypervisors, or virtualization.

You will also be eligible for equity and benefits. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.

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.