Machine Learning Engineer, Autonomy

42dot • San Francisco, CA

1d • $145,000 - $205,000

About The Position

42dot is building a new autonomous driving organization focused on delivering production-ready Level 4 autonomy across trucks, buses, passenger vehicles, and robotaxis. The organization takes an ML-first approach centered on end-to-end learning, foundation models, vision-language-action models, and world models.

As a founding member of the autonomy organization, the Machine Learning Engineer will help build autonomous driving systems and define the platform’s architecture, technical direction, engineering culture, and roadmap. This is a hands-on engineering role involving model development, production coding, failure analysis, and work that runs on real vehicles.

Requirements

• Demonstrated grit, ownership, and problem-solving ability, including taking initiative, thriving in ambiguity, pursuing difficult problems, and delivering results.
• Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
• 1–4 years of experience building machine learning systems, or equivalent research experience.
• Strong Python and PyTorch or JAX skills.
• Strong fundamentals in machine learning, deep learning, computer vision, robotics, or related fields.

Nice To Haves

• Autonomous driving or robotics experience.
• Experience with foundation models, vision-language models, vision-language-action models, end-to-end learning, or world models.
• Experience with distributed training, simulation, or large-scale data processing.
• C++ experience.

Responsibilities

• Develop and train machine learning models for autonomous driving.
• Contribute to end-to-end driving systems, vision-language-action models, and world models.
• Build scene understanding and driving intelligence capabilities.
• Improve training pipelines, evaluation systems, and data workflows.
• Analyze failures and improve model performance.
• Collaborate with software, systems, and vehicle engineering teams.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level