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Freelance Nvidia Autonomous Driving Jobs (NOW HIRING)

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As of Jul 13, 2026, the average hourly pay for freelance nvidia autonomous driving in the United States is $22.97, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $18.75 per hour, depending on experience, location, and employer.
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Senior Software Engineer - Autonomous Driving

NVIDIA AI

Santa Clara, CA โ€ข On-site

$143K - $189K/yr

Full-time

Posted 17 days ago


Job description

Job Summary:
NVIDIA AI is building the software foundation for scalable, high-performance vehicle computing platforms that power autonomous driving and centralized vehicle architectures. They are seeking a Senior Software Engineer to lead architecture and optimization efforts across the autonomous driving software stack, focusing on deep neural network optimization and deployment on NVIDIA automotive compute platforms.
Responsibilities:
โ€ข Lead architecture and technical strategy for optimizing inference workloads in autonomous driving applications.
โ€ข Drive end-to-end performance analysis across DNN models, TensorRT/compiler flows, CUDA kernels, memory behavior, scheduling, runtime services, and automotive platform constraints.
โ€ข Develop and guide model optimization techniques such as quantization, pruning, distillation, graph optimization, operator fusion, kernel selection, and layout/memory optimization.
โ€ข Collaborate with TensorRT, CUDA, compiler, silicon architecture, perception, planning, DriveOS and safety platform teams.
โ€ข Build tools, methodologies, and metrics for profiling, benchmarking, debugging, and validating model and platform performance.
Qualifications:
Required:
โ€ข BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
โ€ข 12+ years of software engineering experience in systems software, AI/ML infrastructure, deep learning inference, compiler/runtime technology, or platform performance.
โ€ข Strong C/C++ and practical Python experience.
โ€ข Deep familiarity with TensorRT, TensorRT-LLM, ONNX, PyTorch, CUDA, Triton, or related frameworks.
โ€ข Experience optimizing DNN models for latency, throughput, memory footprint, and power.
Preferred:
โ€ข Hands-on experience with TensorRT internals, CUDA kernels, Triton kernels, or other compiler/runtime technologies.
โ€ข Experience deploying optimized DNNs, LLMs, VLMs, or perception models on embedded, edge, robotics, or automotive platforms.
โ€ข Background in autonomous driving, ADAS, robotics, real-time systems, safety-aware software, or deterministic low-latency systems.
โ€ข Experience with ISO 26262, QNX, Safe RTOS, DriveOS, Linux, hypervisors, or virtualization.
Company:
Explore the latest breakthroughs made possible with AI. Founded in , the company is headquartered in Santa Clara, CA, US, , with a team of 10001+ employees. The company is currently Late Stage.