Senior ML Compiler Engineer

FluidJobs; United States; Remote; USD 129,000 - 261,000; Full time

Benefits offered by this job

Health and wellbeing benefits

GM vehicle discounts

Tuition assistance

Job summary

General Motors is seeking a Senior Compiler Engineer for the AI Kernels & Compilers team to optimize the model compilation stack for autonomous and assisted driving. You will transform high-level models into fast, reliable inference artifacts across on-vehicle platforms.

You’ll build robust tooling, validate numerical correctness, and surface actionable diagnostics to model authors, advancing the state of the art in real‑world autonomy and safe, scalable deployment.

Qualifications

• 3+ 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).
• Expertise in writing production quality Python/C++ code.
• Expertise in the software development life-cycle - coding, debugging, optimization, testing, integration.

Responsibilities

• 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 fidelity under safety constraints.
• Collaborate closely with kernels, runtime, and hardware teams to co-design interfaces and ensure the compiler exposes the right abstractions for peak performance.
• Set standards and best practices for model export, validation, and debugging for rapid AV iteration.

Skills

Compilers

ML frameworks

Python

C++

SDLC

Education

BS in CS/CE/EE

Tools

ONNX

MLIR

XLA

TVM

TensorRT

CUDA

Job description

About theMission

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 cutting‑edgeperception, prediction, and planning research into production‑grade 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 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 withAI Deployments,AI Solutions, Runtime, andAI Kernelsteams to co‑designaplatform thatenablesnew ideasin researchto bequickly and safelyshippedto production fleets.

You’lljoin a group ofdeepcompiler, systems, and GPU engineerswho enjoyworking onhard problems,anddiving into MLIR/ONNXand CUDA/TensorRTinternals. 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 aSeniorCompiler Engineer on the AI Kernels & Compilers team, you willwork on thecompilation stack that takes high‑level models and turns them into highly optimized inference artifacts running on GM’s autonomous and assisted driving platforms.You’llbe a key contributor to a pipeline andtooling that makesthat path fast, reliable, andeffortlessfor ML engineers across the AV organizationto compile their models.

You willwork on an evolvinga state‑of-the‑artmodel 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 simultaneouslyoptimizecompilation throughput, model fidelity, and on‑vehicle 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 of compilers, performance engineering, and real‑world autonomy , this role puts your decisions directly on the critical path of what runs on the car.

Whatyou’llbe doing (Responsibilities)

• Buildand evolve the model compilation toolchain used to deploy large‑scaleperception, 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.

Your Skills & Abilities (Required Qualifications)

• 3+ 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 andoptimizingONNX‑basedmodelexport 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$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.

• 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.

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