Manager, Deep Learning – Autonomous Vehicles and Robotics

What you'll do

• Lead and develop deep learning engineers delivering inference optimization and model enablement for automotive and robotics customers.
• Own technical customer engagements, including scoping, resource allocation, and delivery of production-quality solutions.
• Set deployment and optimization direction while coordinating with OEM partners and NVIDIA research, compiler, runtime, and hardware teams.

What they ask for

• 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 team leadership experience.
• Strong knowledge of current deep learning architectures and inference optimization toolchains (TensorRT or equivalent).

Nice to have

• Experience leading deep learning optimization teams in autonomous vehicles or robotics with direct OEM or Tier-1 engagement.
• Experience with ML compiler frameworks, inference runtime development, automotive safety standards, or Agentic AI frameworks, tools, and protocols.

Pay

224,000 USD - 356,500 USD (base salary, Level 3); 272,000 USD - 431,250 USD (base salary, Level 4)

Tools

TensorRT, TVM, MLIR, XLA, Triton, LangChain, LangGraph, MCP

AI focus

Leads deep learning model optimization and inference deployment for autonomous vehicles and robotics, including modern architectures such as transformers, vision-language models, state space models, and robotic foundation models.