Senior ML Engineer - Model Compression at General Motors in Austin, TX

Senior ML Engineer - Model Compression Location: Sunnyvale, California, United States of America Job Description About the Team TheCompression and Parity team in GM’sAutonomous Vehicle (AV) Organizationenables repeatable, high-velocitymodeldeploymentsthroughprincipled and automatedmodel compressionunder strict safety guarantees.We partner closely with model developers and deployment and infra engineers to ship numerically robust, low-latency models to the car, blending rigorous analysis withstate-of-the-artmethods and our own innovations. About the Role Over time, you will help grow and evolve the Compression and Parity functionthrough the following: Developing and iterating on quantizationand compressionstrategiesfor ourAV models,consideringmodel numerical properties, safety and latency constraints, andhardware performance, andpartnering on deployment of quantized modelsto NVIDIA‑based AV hardwarewith our deployment, compiler, and kernel teams Advancing our numerical sensitivity analysesto recommend safecompressionpolicies per op/layer/block,using AV-relevant metrics(perception, trajectory,etc.) to evaluate compressed models,andcollaborating withEmbodied AItosupportcompression-aware modeling Evolvingsensitivity analysis, compression, and parity toolinginto a connected, automated flow that makes low‑precision deployments repeatable, reliable, and low‑touch,with an emphasis onrobust execution and maintainability Bridging the gapbetweenstate-of-the-artmodel compressionresearch andsafety-constrained deploymentwhilemakingstrong technical contributions incross-functional projectsand educating others on best practices Your Skills & Abilities (Required Qualifications) Bachelor'sdegreein Computer Science, Electrical Engineering, Physics, Mathematics, Data Science / ML, or a closely related quantitative field (or equivalent experience) 3+ yearsof industry experience focused onmodel optimization and deployment, with significant hands‑on work inneural network quantization / model compression / efficient inference  or relevant experience StrongproficiencyinPyTorchandexperience withgraph‑level representations(e.g.,PyTorchFX, ONNX) for capture and manipulation Background innumerical linear algebra and optimization(conditioning, spectral properties, Jacobians, Hessians) and how they relate to quantization robustness What Will Give You A Competitive Edge (Preferred Qualifications) Master'sor PhD degreein related quantitative fields Deep experience withPTQ and QAT,compression frameworks(e.g.,PT2E,ModelOpt,torchao) andadvanced quantization algorithms(e.g., GPTQ, AWQ,SmoothQuant,QuIP,SparseGPT),as well as with building or extendingquantization toolchains Hands‑on experience designingnumericsobservability and sensitivity toolingintegrated into training or evaluation pipelines (logging ranges, saturation, quant noise, etc.) A track recordof collaboration,includingleading cross-functional initiatives andmentoring others Experience withadditionalcompression techniquessuch as structured/unstructuredpruning,low‑rank decomposition, orknowledge distillation Experience withperceptionand/or transformer‑based models(e.g., multi‑view encoders, BEV backbones, detection/segmentation heads,trajectoryor planning networks), ideally inAV / ADAS General understanding ofkernel performance and optimizationfor reduced precision formats Direct experience withspecialized hardware accelerators foredge deploymenton tight latency and memory budgets (automotive SoCs, robotics platforms, or similar) Published research, open‑source contributions, orothernotable, intellectually curiousworkin quantization, compression, or efficient inference 3+ yearsof industry experience focused onmodel optimization and deployment, with significant hands‑on work inneural network quantization / model compression / efficient inference  or relevant experience 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. #GM-AV-1 This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week {or other frequency dictated by your manager}. The selected candidate will be required to travel <25% for this role. This job may be eligible for relocation benefits. About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Benefits Overview From day one, we're looking out for your well-being–at work and at home–so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources. Non-Discrimination and Equal Employment Opportunities (U.S.) General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. 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