NVIDIA

4 weeks ago

Senior Software Engineer - Autonomous Driving

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Lead architecture and optimization for autonomous driving software, driving performance analysis of DNN models and TensorRT/cuda pipelines, and collaborate across TensorRT, CUDA, compiler, silicon, perception, and safety teams to deploy high-performance automotive AI on NVIDIA compute platforms.

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•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.

Pay and Benefits

Salary: USD 224,000 - 356,500 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•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.

Experience:12+ yearsAutonomous drivingAI/ML infrastructureDeep learning inferenceCompiler/runtime technologyPlatform performance

Education:Bachelor's

Skills:Problem-solvingLeadershipCollaboration

Tech Stack:C++PythonTensorRTCUDAPyTorchONNXTriton

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

4 weeks ago

Senior Software Engineer - Autonomous Driving

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Santa Clara

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•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.

Pay and Benefits

Salary: USD 224,000 - 356,500 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•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.

Experience:12+ yearsAutonomous drivingAI/ML infrastructureDeep learning inferenceCompiler/runtime technologyPlatform performance

Education:Bachelor's

Skills:Problem-solvingLeadershipCollaboration

Tech Stack:C++PythonTensorRTCUDAPyTorchONNXTriton

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor