Director, Deep Learning Solutions

Details

NVIDIA is a world leader in physical AI, powering self-driving cars, humanoid robots, intelligent environments, medical devices and more. Our software platforms are at the core of this mission, enabling innovators to build world-changing products that save lives, improve working conditions, and elevate standards of living across the globe. NVIDIA is looking for an engineering leader who is hands-on with deep learning—comfortable reading/modeling code, not just running it. You bring strong intuition for modern architectures (e.g., transformers, diffusion), deep experience tuning for NVIDIA GPUs (kernels, memory, latency/efficiency trade-offs) / SoCs, and a proven record delivering robust, low-latency inference at scale. You have led teams that turn SOTA models into reliable, measurable business impact for embedded platforms. You will inherit a cohesive, high-performing team that’s been built and refined over the past eight years.

Responsibilities

• Drive strategic implementations of TensorRT inference solutions for edge devices: lead TensorRT releases and solutions for key verticals, including game consoles, robotics and autonomous vehicles for Jetson, DRIVE and GPU + x86 hardware platforms. Set up Proofs of Readiness (PORs) and guide their implementations.
• Coordinate the development and release of Torch-TRT and other alternative optimization frameworks like MLIR-TRT.
• Lead customer solutions: collaborate with major automotive and robotics OEMs and partners to adjust and optimize custom deep learning models for their specific requirements. Provide direct customer support, including debugging, technical education, and handling customer inquiries for Automotive and Robotics partners. Draft, negotiate, and finalize statements of work (SOWs) with customers and partners.
• Performance benchmarking: orchestrate efforts to achieve leading performance results on industry benchmarks like MLPerf on various edge devices.
• Technical leadership & influence: function as a technical leader for deep learning across multiple teams, providing oversight and build support. Apply customer insights to influence the composition and structure of upcoming SoC deep learning hardware.
• Scale the team: strategically hire to meet new demands while mentoring and adjusting existing teams to new deep learning challenges.
• Represent NVIDIA Deep Learning Solutions in webinars, conferences and partner events.

Requirements

• PhD or equivalent experience in Computer Science / Electrical Engineering (or equivalent experience).
• A minimum of 8 years of meaningful involvement in machine learning / deep learning research or practical experience, coupled with 8+ years of leadership background and overall 15+ years of industry experience.
• Over 10 years of validated expertise in the embedded software sector, holding technical leadership positions accountable for delivering outstanding production software in complex settings.
• Solid understanding of embedded operating system internals (QNX, Linux), memory management, C / C++, and embedded / system software concepts.
• Background in parallel programming (e.g., CUDA, OpenMP).
• Deep knowledge of GPU, CPU and dedicated deep learning architecture fundamentals and low-level performance optimizations using heterogeneous computing.

Ways to Stand Out

• Leadership role in production deployment of autonomous solutions for passenger cars, with deep understanding of constraints and advancements of sensing, computing, and model architecture evolutions.
• Experience leading globally distributed teams.
• Experience with automotive safety standards.

Compensation & Benefits

• Base salary ranges provided by level:
  • Level 5: 308,000 USD - 471,500 USD
  • Level 6: 368,000 USD - 557,750 USD
• You will also be eligible for equity and benefits (see NVIDIA benefits page).

Other Details

• Location: San Jose, CA, United States.
• Employment type: Full time.
• Applications for this job will be accepted at least until October 18, 2025.
• NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer.