Remote Senior Manager, AI Deployment (Autonomous Driving)

General Motors; United States; Remote; USD 296.000 - 454.000; Vollzeit

Benefits dieser Stelle

Remote work

Travel <25%

Relocation benefits

Health and wellbeing benefits

Zusammenfassung

General Motors is seeking a Senior Manager, AI Deployment to lead the strategy and execution of model performance and on-vehicle inference for autonomous driving. You will lead engineering managers and senior technical leaders across model optimization, GPUs, and runtimes, balancing latency, memory, throughput, and power.

The role is categorized as remote in the United States, with travel up to 25% and relocation benefits for eligible candidates.

Qualifikationen

• Bachelor's degree in CS, EE, Robotics, ML or related field; advanced degree preferred, or equivalent experience.
• 10+ years of experience in machine learning systems, model optimization, inference, GPU systems, robotics, or autonomous driving.
• 5+ years of people leadership, including leading managers or senior technical leaders.
• Experience shipping production ML inference systems on GPU, accelerator, robotics, automotive, or edge hardware.
• Strong understanding of architecture, tensor shapes, operators, kernels, memory movement, scheduling,_runtime execution, and hardware utilization.
• Hands-on 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, telemetry, dashboards, or profiling workflows.
• Strong systems thinking, communication, decision-making, and cross-functional leadership.

Aufgaben

• 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.
• Build and lead an inclusive, high-performing organization through hiring, coaching, feedback, and manager development.
• Establish clear ownership, priorities, staffing plans, and operating rhythms across performance workstreams.
• Define and manage KPIs for inference latency, latency variability, throughput, memory efficiency, GPU utilization, parity, and regression rate.
• Balance near-term production needs with longer-term investments in profiling, optimization automation, reduced precision, and performance infrastructure.
• Resolve cross-functional issues and align stakeholders when performance, quality, or implementation trade-offs are contested.
• Develop technical leaders and succession plans in GPU performance, model optimization, inference systems, and numerical analysis.

Kenntnisse

ML systems expertise

People leadership

Model optimization

Inference for production

Edge hardware experience

C++ / Python

Strong systems thinking

Ausbildung

Bachelor's degree in Computer Science, Electrical/Computer Engineering, Robotics, ML, or related field

Advanced degree preferred, or equivalent experience

Tools

PyTorch

CUDA

TensorRT

GPU profiling tools

Benchmarking tools

Jobbeschreibung

General Motors is seeking a Senior Manager, AI Deployment to lead the strategy and execution of model performance and on-vehicle inference for autonomous driving. You will lead engineering managers and senior technical leaders across model optimization, GPUs, and runtimes, balancing latency, memory, throughput, and power.

The role is categorized as remote in the United States, with travel up to 25% and relocation benefits for eligible candidates.