Remote Senior AI Deployment Lead, Autonomous Driving

General Motors; Sunnyvale (CA); On-site; USD 296,000 - 454,000; Full time

Benefits offered by this job

Health insurance

Retirement savings plan

Paid vacation & holidays

Job summary

General Motors is seeking a Senior Manager, AI Deployment to drive strategy and execution for model performance and on-vehicle inference in autonomous driving. You will lead engineering managers across model optimization, GPU systems, and runtime execution, setting latency budgets and guiding architecture decisions.

The role requires strong technical judgment, people leadership, and the ability to balance latency, memory, throughput, and power.

Qualifications

• Bachelor’s degree in Computer Science, Electrical or Computer Engineering, Robotics, Machine Learning, or related field.
• 10+ years of experience in ML systems, model optimization, inference, GPU systems, robotics, autonomous driving, or related field.
• 5+ years of people-leadership experience including leading managers or senior technical leaders.
• Experience shipping production ML inference systems on GPU, accelerator, robotics, automotive, or edge hardware.
• Strong understanding of model performance factors: architecture, tensor shapes, operators, kernels, memory movement, scheduling, runtime execution, hardware utilization.
• Hands-on experience with PyTorch, CUDA, C++, Python, TensorRT, GPU profiling, benchmarking, performance analysis, or inference runtimes.
• Experience with quantization, pruning, distillation, architecture optimization, kernel optimization, or memory optimization.
• Experience building benchmark automation, performance regression detection, telemetry, dashboards, or profiling workflows.
• Strong systems thinking, communication, decision-making, and cross-functional leadership skills.

Responsibilities

• Own the strategy, roadmap, and operating plan for AI model performance and inference quality.
• Establish performance budgets for latency, throughput, memory, GPU utilization, power, and numerical parity.
• Lead investigations into performance bottlenecks across model architecture, operators, kernels, memory movement, scheduling, runtime behavior, and hardware utilization.
• Establish repeatable benchmarking and profiling practices across simulation, hardware-in-the-loop, bench, and vehicle environments.
• Guide optimization through model architecture changes, operator and kernel improvements, memory optimization, scheduling, and hardware-aware execution.
• Build performance dashboards, regression detection, benchmark automation, and root-cause diagnostics.
• Partner with Embodied AI, model development, GPU kernel, runtime, system performance, vehicle integration, simulation, and safety teams.
• Influence model design by translating profiling results into clear recommendations for model architects and researchers.
• Represent AI Deployment in architecture reviews, program planning, and senior leadership discussions.

Skills

PyTorch

CUDA

C++

Python

TensorRT

GPU profiling

Education

Bachelor’s degree in CS/EE/Robotics/ML

Advanced degree preferred

Tools

NVIDIA Nsight Systems

NVIDIA Nsight Compute

PyTorch Profiler

TensorRT profiling tools

Job description

General Motors is seeking a Senior Manager, AI Deployment to drive strategy and execution for model performance and on-vehicle inference in autonomous driving. You will lead engineering managers across model optimization, GPU systems, and runtime execution, setting latency budgets and guiding architecture decisions.

The role requires strong technical judgment, people leadership, and the ability to balance latency, memory, throughput, and power.