Ml Compiler Engineer Jobs in Texas (NOW HIRING)

AbouttheMission

GM'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-drivingsystems,tomove us toward safer, more sustainable, and more accessible mobility.

For theAIKernels & Compilers team, that mission shows up in the details: turning cuttingedgeperception, prediction, and planning research into productiongrade software that can run efficiently and reliably on real vehicles at scale. We pioneernew approachesto 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 andkernelsworktodirectlyinfluencehow automated vehicles understand and react to the world - whileoperatingatthesafety,reliabilityand scaleof a company like GM - this is where that impact becomes real.

About the Team

The AI Compiler team sits at the heart of how advanced AI models make it onto the car. We own the compiler that turns highlevel models into fast, reliable inference across GPUs powering GM's nextgeneration 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 onvehicle workloads while preserving correctness and robustness in realworld conditions. We partner closely withAI Deployments,AI Solutions, Runtime, andAI Kernelsteams to codesignaplatform thatenablesnew ideasin researchto bequickly and safelyshippedto production fleets.

You'lljoin a group ofdeepcompiler, systems, and GPU engineerswho enjoyworking onhard problems, diving into MLIR/ONNXand CUDA/TensorRTinternals, and mentoring others on performance engineering. 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.

The Role

As a Staff Compiler Engineer on the AI Kernels & Compilers team, you will own the endtoend compilation stack that takes highlevel models and turns them into highly optimized inference artifacts running on GM's autonomous and assisted driving platforms.You'lldefine the technical vision and build the tooling that makes that path fast, reliable, andeffortlessfor ML engineers across the AV organizationto compile their models.

You will design and evolve ourmodel export and compilation pipeline-from capturing highlevel model graphs, through intermediate representations and compiler transforms, into acceleratorspecific inference engines and their integration with our runtime-so that we can simultaneouslyoptimizecompilation throughput, model fidelity, and onvehicle latency. Along the way,you'llbuild robust tooling tovalidatenumerical correctness,detectand bisect performance regressions, and surface clear, actionable diagnostics back to model authors.

If you want to work at the intersection ofcompilers, performance engineering, and realworld autonomy, this role puts your decisions directly on the critical path of what runs on the car.

WhatYou'llDo

• Own and evolvethe model compilation toolchain used to deploy largescaleperception, prediction, and planning models to the AV.

• Architect new compiler passes and analysisthat 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 teamsto codesign interfaces, shape accelerator capabilities, and ensure the compiler exposes the right abstractions to unlock peak performance on each platform.

• Set standards and best practicesfor model export, validation, and debugging so that AV teams can iterate quickly with clear, reproducible performance and accuracy characteristics.

Your Skills & Abilities (Required Qualifications)

• 5+ years of experience in the field of compilers

• Experience with ML frameworks (e.g.,PyTorch, TensorFlow, JAX) and software stack (e.g.,ONNX,MLIR, XLA, TVM,TensorRT,etc)

• Expertisein writing production quality Python/C++ code

• Expertisein the software development life-cycle - coding, debugging, optimization, testing, integration

• BS, or higher degree, in CS/CE/EE, or equivalent

What Will Give YouACompetitive Edge (Preferred Qualifications)

• Experience building andoptimizingONNXbasedmodelexport and deployment pipelines

• GPU programming (CUDA) and familiarity with ML SW stack (e.g.,cuDNN,cuBLAS)

• Experience with ML accelerators and hardware architecture

• Experience developing and deploying machine learning models

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

• The salary range for this role: is$185,100 to $335,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

• Benefits: 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.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

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