Hybrid Machine Learning Systems Engineer – Autonomous Driving

Posted last month

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About the role

  • Intern optimizing AI training platform for autonomous driving at GM. Developing infrastructure and tools for model training and enhancing testing infrastructure.

Responsibilities

  • Develop scalable infrastructure and tools to support model training, regression, and rules-based models.
  • Suggest, collect and synthesize requirements and create effective feature roadmap.
  • Code deliverables in tandem with the engineering team.
  • Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU).
  • Perform specific responsibilities which vary by team.

Requirements

  • Currently enrolled in a full-time, degree-seeking program and in the process of obtaining a Bachelor's degree in computer science or a related technical field.
  • Research and/or work experience in a relevant field, such as machine learning, deep learning, reinforcement learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, or computer vision.
  • Experience in systems software or algorithms.
  • Experience with modern object-oriented programming languages (e.g., Java, C++, Python).
  • Strong communication skills with experience collaborating across cross-functional teams.
  • Able to work fulltime, 40 hours per week.

Benefits

  • Paid US GM Holidays
  • GM Family First Vehicle Discount Program
  • Result-based potential for growth within GM

Job title

Machine Learning Systems Engineer – Autonomous Driving

Job type

Experience level

Entry level

Salary

$7,300 - $8,600 per month

Degree requirement

Bachelor's Degree

Tech skills

Location requirements

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