ML Intern on Sensor Encoder Team

Job Description

To help facilitate administration of relocation benefits if you are selected, please apply using the permanent address you would move from.

Work Arrangement:

Hybrid: This internship is categorized as hybrid. The selected intern is expected to report to the office up to three times per week or as determined by the team.

Locations:

San Francisco, California

Sunnyvale, California

Mountain View, California

About the Team:

The Sensor Encoder team is dedicated to advancing the state-of-the-art in AI for autonomous vehicles, with a specific focus on encoders for camera, lidar and radar. We are a collaborative, forward-thinking group of researchers and engineers tackling some of the most complex challenges in autonomy and machine learning related to sensor data processing.

About the Role:

As an intern on the sensor encoder team, you’ll work on cutting-edge projects advancing vehicle autonomy, developing algorithms and models that shape the future of self-driving technology. This internship provides experience with real-world AI/ML systems, collaboration with leading researchers and engineers, and mentorship from experienced AV researchers to grow your skills in the autonomous vehicle industry.

What You’ll Do:

• Lead research and prototyping of advanced machine learning methods, such as foundation models, vision-language architectures, self-supervised learning.
• Prototype ML models that improve perception, prediction, or decision-making for autonomous driving.
• Collaborate with cross-functional teams, including research, robotics, and systems engineering.

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• Participate in technical discussions, share insights, and work towards publishing results.
  
  
  

Required Qualifications:

• Currently pursuing or in the process of obtaining a Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field.
• Solid understanding of modern machine learning techniques, especially deep learning architectures (e.g., transformers, generative models, multimodal learning).
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Research experience in AI/ML, demonstrated through coursework, academic projects, or publications.
• Strong problem-solving skills and a collaborative mindset.
• Strong communication and presentation skills.
• Experience working and communicating cross functionally in a team environment.
• Able to work fulltime, 40 hours per week
  
  
  

Preferred Qualifications:

• Familiarity with autonomous vehicles or advanced driver assistance systems (ADAS).

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• Experience working with large-scale datasets and training ML models in high-performance computing environments.
• Intent to return to degree program after the completion of the internship/co-op
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, CVPR, ICML, ICLR, AAAI, ECCV, RSS, ICRA, CoRL, or similar.
• Demonstrated experience and self-driven motivation in solving analytical problems using quantitative approaches
• Graduating between December 2026 and June 2027.
  
  
  

Compensation:

• The monthly salary range for this role is $13,100 per month
• GM will provide a one-time lump sum taxable stipend payment to eligible students selected for the 2026 Student Program.
  
  
  

What you’ll get from us (Benefits):

• Paid US GM Holidays
• GM Family First Vehicle Discount Program

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• Result-based potential for growth within GM
• Intern events to network with company leaders and peers
  
  
  

About GM

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Benefits Overview

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