Machine Learning Engineer, AI Inference Solutions (Early in Career)

General Motors is a global leader in advanced driver assistance and autonomous-vehicle technology. The Machine Learning Engineer will help build ML deployment platforms, optimize models for on-vehicle inference, and support production deployments for GM’s Super Cruise fleet. The role includes collaborating with senior engineers and cross-functional teams on performance, reliability, safety, and inference solutions.

Responsibilities:

• Contribute production code across the ML deployment platform, model-optimization workflows, and inference benchmarking/profiling infrastructure
• Pair with senior engineers on deployment workflows, performance investigations, model-optimization experiments (e.g., quantization, pruning, distillation), and platform tooling
• Build, test, and maintain platform tools (e.g., validators, performance probes, parity and sensitivity analyzers, agentic specialists) with technical guidance and code review support
• Investigate and help root-cause production deployment or performance issues; learn and apply the diagnostic playbook for compiler, kernel, runtime, and parity bugs
• Collaborate with cross-functional teams across the AV organization; including kernels, compiler, reduced-precision, parity, and model-development groups—to plan and execute model deployments to the AV stack, working under the guidance of senior engineers
• Participate in code reviews, design discussions, and technical documentation to ensure reliability, correctness, and clear abstractions in a large-scale codebase
• Learn and follow secure coding, safety, and compliance practices required for on-vehicle autonomous driving software