Manager, Deep Learning – Autonomous Vehicles and Robotics

Details

Join NVIDIA's Deep Learning Engineering team within the Tegra Solutions Engineering organization. The team delivers production-quality deep learning solutions for autonomous vehicles and robotics on edge hardware, working at the intersection of modern model architectures, compiler technology, and embedded deployment. Application areas include end-to-end autonomous driving, vision-language-action models, multi-camera perception, and robotic foundation models.

The role leads strategic technical initiatives and works directly with automotive OEMs and robotics partners to solve optimization challenges on NVIDIA DRIVE and Jetson platforms. It also involves collaboration with NVIDIA Research, hardware, and compiler teams to advance deep learning for physical AI.

Responsibilities

• Lead and develop a team of deep learning engineers delivering inference optimization and model enablement solutions for automotive and robotics customers.
• Drive end-to-end technical engagements with OEM partners, including scoping, resource allocation, and delivery of production-quality solutions.
• Set technical direction for optimizing and deploying modern architectures, including transformers, vision-language models, and state space models, on GPU and system-on-chip platforms.
• Partner with compiler, runtime, and hardware teams to connect customer workload patterns with platform capabilities and roadmap priorities.
• Collaborate with NVIDIA Research and internal deep learning teams to bring new techniques into production.
• Represent NVIDIA externally at partner reviews, conferences, and industry forums.

Requirements

• Master's degree or equivalent experience in Computer Science, Electrical Engineering, or a related field.
• At least 8 years of overall experience, including at least 5 years in deep learning model optimization, inference engineering, or neural network compilation.
• At least 4 years of team leadership experience.
• Proven ability to manage concurrent technical customer engagements and deliver under production constraints.
• Strong knowledge of current deep learning architectures and inference optimization toolchains such as TensorRT or equivalent.
• Excellent communication skills, with the ability to engage credibly with OEM engineering leadership and deep technical individual contributors.

Preferred Qualifications

• Experience leading deep learning optimization teams in the autonomous vehicle or robotics domain, with direct OEM or Tier-1 engagement.
• Background in training pipeline optimization, curriculum design, or end-to-end autonomous driving architectures.
• Experience with ML compiler frameworks such as TVM, MLIR, XLA, or Triton, or with inference runtime development.
• Familiarity with automotive safety standards including ISO 26262 and SOTIF and their implications for inference system design.
• Experience building engineering teams in competitive talent markets.
• Experience with agentic AI frameworks, tools, and protocols such as LangChain, LangGraph, and MCP, or equivalent experience.

Team

The Deep Learning Engineering team within Tegra Solutions Engineering works end-to-end, from architecture decisions with OEM engineering leadership through optimization and deployment on DRIVE and Jetson platforms to production vehicles and robots operating in the field. The team works with automotive and robotics companies on network architectures, training infrastructure, inference optimization, and closed-loop simulation, collaborating closely with NVIDIA Research, NVIDIA AI teams, and hardware teams.

Compensation and Benefits

The base salary range is USD 224,000–356,500 for Level 3 and USD 272,000–431,250 for Level 4. Compensation is determined based on location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.

Applications will be accepted at least until April 26, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.