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Sunnyvale, California, United States of America, United States of America
Hybrid
Job Description
The Role
We are looking for an ML tooling engineer to build tools to analyze and optimize distillation, training, and inference of ML models. You will develop and enhance GM's internal ML tooling for high performance software by leveraging state of the art tools like Nsight Systems, PyTorch, etc.
The Autonomous Vehicle (AV) software stack heavily relies on machine learning models to perform critical driving tasks. These cutting-edge custom ML models require an ecosystem of in-house tooling to analyze and improve them. In this role, you will collaborate closely with engineers and researchers from different AV Engineering teams (e.g., Computer Vision, Perception, Behavioral Prediction) to scope out system requirements, while engaging with AV hardware teams to understand the target hardware platform and its constraints.
What You’ll Be Doing (Responsibilities)
Identify new opportunities to improve both training and inference efficiency
Build workflows for correctness and performance analysis on physical in-car compute and sensors
Build tooling to predict model performance based on architecture and data shape
Build tooling to trace actual performance on large distributed training and distillation jobs, running on the world’s most powerful GPUs, and analyze the results
Continually evolve the toolchain and stack, to leverage the latest advancements in AI
Influence model architecture decisions and strategy within GM
Your Skills & Abilities (Required Qualifications)
3+ years of experience in the field of AI/ML
Experience with ML frameworks (e.g., PyTorch, TensorFlow) and NVIDIA developer ecosystem (TensorRT, Nsight-systems, Nsight-compute))
Expertise in writing production quality Python/C++ code
Expertise in the software development life-cycle - coding, debugging, optimization, testing, integration
BS, or higher degree, in CS/CE/EE, or equivalent
What Will Give You A Competitive Edge (Preferred Qualifications)
Experience developing and deploying machine learning models
GPU programming (CUDA) and familiarity with ML SW stack (e.g., cuDNN, cuBLAS)
Experience with ML accelerators and hardware architecture
3+ years of experience in the field of AI/ML 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 $144,700 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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