Manager, Deep Learning – Autonomous Vehicles And Robotics

Details

Join the Deep Learning Engineering team within NVIDIA's Tegra Solutions Engineering organization, where the team delivers production-quality deep learning solutions for autonomous vehicles and robotics on edge hardware. You will lead a group of deep learning engineers 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. You will define and drive strategic technical initiatives and work directly with automotive OEMs and robotics partners to solve optimization challenges on NVIDIA DRIVE and Jetson platforms.

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, owning scoping, resource allocation, and delivery of production-quality solutions.
• Set technical direction on how modern architectures (transformers, vision-language models, state space models) are optimized and deployed on GPU and SOC 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.
• 8+ years of overall experience with at least 5 years in deep learning model optimization, inference engineering, or neural network compilation.
• 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 (TensorRT or equivalent).
• Excellent communication skills with the ability to engage credibly with both OEM engineering leadership and deep technical individual contributors.

Ways to stand out

• 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 (TVM, MLIR, XLA, Triton) or inference runtime development.
• Familiarity with automotive safety standards (ISO 26262, SOTIF) and their implications for inference system design.
• Track record of building engineering teams in competitive talent markets and experience with Agentic AI frameworks, tools, and protocols like LangChain, LangGraph, MCP or equivalent.

Team and context

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. Engineers engage directly with leading automotive and robotics companies and collaborate closely with NVIDIA Research, various NVIDIA AI teams, and hardware teams. The team is growing with presence across multiple sites.

Compensation and benefits

• Base salary range (Level 3): 224,000 USD - 356,500 USD per year.
• Base salary range (Level 4): 272,000 USD - 431,250 USD per year.
• You will also be eligible for equity and benefits.

Other

• Applications for this job will be accepted at least until April 26, 2026.
• This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.