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General Motors

Senior Machine Learning Engineer

Reposted Yesterday
Remote or Hybrid
Hiring Remotely in United States
134K-205K Annually
Senior level
Remote or Hybrid
Hiring Remotely in United States
134K-205K Annually
Senior level
Develop machine learning and reinforcement learning models for autonomous vehicles. Streamline integration, create ML infrastructure, and optimize training loops. Collaborate on AV technology.
The summary above was generated by AI
Description
Remote: This role is based remotely but if you live within a 50-mile radius of Atlanta, Austin, Detroit, Warren, Milford or Mountain View, you are expected to report to that location three times a week, at minimum.
Role: The Smart Agents group is responsible for building the ML models and system to simulate road users in a variety of situations and generate the scenarios used for testing and training AV driving policies. If you think of Simulation as a video game our autonomous vehicles train on to learn to drive, the Smart Agents team develops the ML/AI models that control the other characters in the video game to interact in realistic ways as the av drives-eg, the other vehicles, bikers, and pedestrians. Our technology stack includes Generative AI models (GPT) and Reinforcement Learning (RL) policies. The Smart Agents group work closely with the rest of the Simulation, and our partners Behaviors, Perception, and Safety Engineers.
The specific duties may include ML/RL model development as well as training loop development, streamlining optimization, integration, creating ML infrastructure, metrics, and data pipelines for production model deployment as well as for fast experimentation cycles. This team is critical to the testing and training of our autonomous vehicles.
What You'll Do:
  • Develop machine learning (ML) and reinforcement learning (RL) models, including training loop development and optimization.
  • Streamline integration and create ML infrastructure, metrics, and data pipelines for production model deployment and rapid experimentation.
  • Contribute as a full-stack Machine Learning Engineer (MLE) with strong software engineering (SWE) skills, focusing on engineering and applied ML.
  • Support the ML team in accelerating project timelines, particularly in areas related to Autopilot, Lane Keep, and autonomous vehicle (AV) technologies.
  • Experience in simulation and robotics is highly desirable, with a preference for candidates from AV or robotics backgrounds rather than solely cloud-focused companies.

Additional Description
Your Skills & Abilities:
  • 4+ years of experience in the field of robotics or latency-sensitive backend services

  • Proven experience in machine learning and classification. Familiar with ML frameworks such as Tensorflow or PyTorch

  • Experience building highly performant ML and system pipelines

  • Strong programming skills in modern C++ or Python

  • Experience with profiling CPU and/or GPU software, process scheduling, and prioritization

  • Passionate about self-driving car technology and its impact on the world

  • Expertise in setting architectures that are scalable, efficient, fault-tolerant, and are easily extensible allowing for changes overtime without major disruptions.

  • Ability to design across multiple systems. Ability to both investigate in sophisticated areas as well as a good breadth of understanding of systems outside of your domain.

  • Ability to wear several hats shifting between coding, design, technical strategy, and mentorship combined with excellent judgment on when to switch contexts to meet the greatest need.

  • Track record in deploying perception/prediction/av models into real world environments

  • Experience working with RL and sequence prediction (ML) 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 $134,000 to $205,000. 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.

Relocation: This job may be eligible for relocation benefits.
#LI-MH2
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.
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Non-Discrimination and Equal Employment Opportunities (U.S.)
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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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Top Skills

C++
Machine Learning
Python
PyTorch
Reinforcement Learning
TensorFlow

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