Senior Manager, AI Inference & Deployment Lead

Relha LLC; Northern (KY); Hybrid; USD 296,000 - 454,000; Full time

Job summary

General Motors is spearheading AI foundations for autonomous driving, focusing on model optimization, GPU systems, and on-vehicle inference. The Senior Manager will lead engineering managers and researchers to drive latency, memory, and numerical parity improvements across simulation, hardware-in-the-loop, bench, and vehicle environments.

The role requires deep technical judgment, people leadership, and the ability to balance latency, throughput, power, and accuracy while guiding architecture

Qualifications

• Bachelor’s degree or higher in a technical field.
• 10+ years of ML systems, model optimization, inference, or robotics experience.
• 5+ years of people leadership.

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 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.

Skills

Model optimization

GPU systems

Inference

Leadership

PyTorch

CUDA

C++

Python

TensorRT

Profiling

Education

Bachelor’s degree in Computer Science, Electrical or Computer Engineering, Robotics, Machine Learning, or related field

Tools

PyTorch

CUDA

C++

Python

TensorRT

GPU profiling

Job description

General Motors is spearheading AI foundations for autonomous driving, focusing on model optimization, GPU systems, and on-vehicle inference. The Senior Manager will lead engineering managers and researchers to drive latency, memory, and numerical parity improvements across simulation, hardware-in-the-loop, bench, and vehicle environments.

The role requires deep technical judgment, people leadership, and the ability to balance latency, throughput, power, and accuracy while guiding architecture