Machine Learning Engineer

Senior Compiler EngineerGM's vision of Zero Crashes, Zero Emissions, and Zero Congestion guides everything we do in autonomous and assisted driving. The AV organization is building advanced automated driving technologies, including Level 4–capable fully self-driving systems, to move us toward safer, more sustainable, and more accessible mobility.For the AI Kernels & Compilers team, that mission shows up in the details: turning cutting-edge perception, prediction, and planning research into production-grade software that can run efficiently and reliably on real vehicles at scale. We pioneer new approaches to model export, kernel development, and performance engineering so that every cycle on our accelerators translates into better situational awareness, faster reaction times, and more robust behavior on the road.If you want your compiler and kernels work to directly influence how automated vehicles understand and react to the world — while operating at the safety, reliability and scale of a company like GM — this is where that impact becomes real.The AI Compiler team sits at the heart of how advanced AI models make it onto the car. We own the compiler that turns high-level models into fast, reliable inference across GPUs powering GM's next-generation autonomous and assisted driving features.Our work spans graph lowering, operator coverage, kernel integration, and deployment tooling, with a mandate to squeeze every millisecond out of on-vehicle workloads while preserving correctness and robustness in real-world conditions. We partner closely with AI Deployments, AI Solutions, Runtime, and AI Kernels teams to co-design a platform that enables new ideas in research to be quickly and safely shipped to production fleets.You'll join a group of deep compiler, systems, and GPU engineers who enjoy working on hard problems, and diving into MLIR/ONNX and CUDA/TensorRT internals. We value clear thinking, strong engineering fundamentals, and a culture where people can do the best work of their careers on problems that directly shape the future of automated driving.As a Senior Compiler Engineer on the AI Kernels & Compilers team, you will work on the compilation stack that takes high-level models and turns them into highly optimized inference artifacts running on GM's autonomous and assisted driving platforms. You'll be a key contributor to a pipeline and tooling that makes that path fast, reliable, and effortless for ML engineers across the AV organization to compile their models.You will work on an evolving state-of-the-art model export and compilation pipeline —from capturing high-level model graphs, through intermediate representations and compiler transforms, into accelerator-specific inference engines and their integration with our runtime— so that we can simultaneously optimize compilation throughput, model fidelity, and on-vehicle latency. Along the way, you'll build robust tooling to validate numerical correctness, detect and bisect performance regressions, and surface clear, actionable diagnostics back to model authors.If you want to work at the intersection of compilers, performance engineering, and real-world autonomy, this role puts your decisions directly on the critical path of what runs on the car.Build and evolve the model compilation toolchain used to deploy large-scale perception, prediction, and planning models to the AV.Architect new compiler passes and analysis that improve build times, memory footprint, and runtime latency while preserving—or intentionally trading off—fidelity under strict safety and reliability constraints.Collaborate closely with kernels, runtime, and hardware teams to co-design interfaces, shape accelerator capabilities, and ensure the compiler exposes the right abstractions to unlock peak performance on each platform.Set standards and best practices for model export, validation, and debugging so that AV teams can iterate quickly with clear, reproducible performance and accuracy characteristics.3 + years of experience in the field of compilersExperience with ML frameworks (e.g., PyTorch, TensorFlow, JAX) and software stack (e.g., ONNX, MLIR, XLA, TVM, TensorRT, etc.)Expertise in writing production quality Python/C++ codeExpertise in the software development life-cycle - coding, debugging, optimization, testing, integrationBS, or higher degree, in CS/CE/EE, or equivalentExperience building and optimizing ONNX-based model export and deployment pipelinesGPU programming (CUDA) and familiarity with ML SW stack (e.g., cuDNN, cuBLAS)Experience with ML accelerators and hardware architectureExperience developing and deploying machine learning modelsThe salary range for this role: is $128,700 to $261,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.An incentive pay program offers payouts based on company performance, job level, and individual performance.GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}. The selected candidate will be required to travel <25% for this role. This job may be eligible for relocation benefits.