General Motors

Senior AI/ML Tooling Engineer

Sunnyvale, California, United States of America Full time

Job Description

Senior AI/ML Tooling Engineer

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 Do
  • 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
Additional Description
Your Skills & Abilities:
  • 5+ 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
  • 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

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.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws. 

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

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