VLA Model Development Intern - Autonomous Driving Research

cariadinc; Mountain View (CA); Vor Ort; USD 62.000 - 132.000; Teilzeit

Zusammenfassung

CARIAD invites applications for an Engineer I, VLA Model Development Internship in Mountain View, CA. You will support model research and development for autonomous driving, focusing on vision-language-action models, perception, or world models.

This role involves prototyping, training, data preparation, and rigorous evaluation with a mentor. Ideal candidates are pursuing or holding a Master's or PhD in Computer Science, with strong Python and PyTorch skills, and a track record in deep learning

Qualifikationen

• Strong Python programming skills and practical experience with PyTorch or an equivalent deep learning framework.
• Foundations in deep learning, linear algebra, probability, and experimental design.
• Hands-on experience in at least one area: vision-language-action models, computer vision / perception, or world models.
• Ability to prepare datasets, train or fine-tune models, debug failures, and evaluate results reproducibly.

Aufgaben

• Prototype, train, and fine-tune VLA models or supporting perception and world-model components.
• Prepare driving datasets and evaluation splits; improve data quality and coverage.
• Run controlled experiments and ablations and maintain reproducible configurations and experiment records.
• Document methods, results, and limitations; review code and present findings.

Kenntnisse

Analytical thinking

Structured problem solving

Written and verbal communication

Ausbildung

Master's or PhD in Computer Science

Tools

Python

PyTorch

Transformers

GPU training

Jobbeschreibung

CARIAD invites applications for an Engineer I, VLA Model Development Internship in Mountain View, CA. You will support model research and development for autonomous driving, focusing on vision-language-action models, perception, or world models.

This role involves prototyping, training, data preparation, and rigorous evaluation with a mentor. Ideal candidates are pursuing or holding a Master's or PhD in Computer Science, with strong Python and PyTorch skills, and a track record in deep learning