Manager, Deep Learning – Autonomous Vehicles and Robotics

Description

You will lead the deep learning engineering team in the company's Tegra solutions engineering organization, which builds production-ready deep learning systems for autonomous vehicles and robots that run on edge hardware.

The work covers end-to-end self-driving models, vision-language-action models, multi-camera perception, and robot foundation models.

You will set the technical direction for strategic initiatives and work directly with car makers and robotics partners on their hardest optimization problems on the company's automotive and embedded robotics platforms.

The team works with the company's research, hardware, and compiler groups to move new deep learning methods into products.

The team is growing and is expanding across several sites. Its work ships in real vehicles and robots operating in the field.

Responsibilities

• Lead and grow a group of deep learning engineers who optimize inference and enable models for automotive and robotics customers.
• Own partner projects from scoping and staffing through to delivery of production-ready solutions.
• Decide how modern architectures such as transformers, vision-language models, and state space models get optimized and deployed on GPU and system-on-chip platforms.
• Work with compiler, runtime, and hardware teams to match customer workload patterns to platform features and the product roadmap.
• Work with research and internal deep learning teams to bring new techniques into production.
• Represent the company externally at partner reviews, conferences, and industry forums.

Requirements

• A master's degree or equivalent experience in computer science, electrical engineering, or a related field.
• 8+ years of overall experience, including at least 5 years in deep learning model optimization, inference engineering, or neural network compilation.
• 4+ years of experience leading a team.
• A record of managing several technical customer engagements at once and delivering 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 work credibly with both OEM engineering leaders and senior individual contributors.
• Ways to stand out from the crowd: experience leading deep learning optimization teams in autonomous vehicles or robotics, with direct work with OEMs or Tier-1 suppliers.
• Ways to stand out from the crowd: background in training pipeline optimization, curriculum design, or end-to-end autonomous driving architectures.
• Ways to stand out from the crowd: experience with ML compiler frameworks such as TVM, MLIR, XLA, or Triton, or with inference runtime development.
• Ways to stand out from the crowd: familiarity with automotive safety standards ISO 26262 and SOTIF and how they affect inference system design.
• Ways to stand out from the crowd: experience building engineering teams in competitive talent markets, and experience with agentic AI frameworks, tools, and protocols such as LangChain, LangGraph, MCP, or equivalent.

Conditions

Base salary depends on location, experience, and other objective job-related factors.

Level 3 base salary range: 224,000 USD to 356,500 USD.

Level 4 base salary range: 272,000 USD to 431,250 USD.

This posting is for an existing vacancy, and applications will be accepted at least until November 3, 2026.

The company uses AI tools in its recruiting process.

The company is an equal opportunity employer and does not discriminate on the basis of any characteristic protected by law.