Applied Deep Learning Algorithm Intern, Autonomous Driving - 2027
Core
Develop, train, and evaluate learning-based algorithms for autonomous driving decision-making, planning, and behavior using supervised fine-tuning, reinforcement learning, and Transformer-based approaches.
Role type
Applied Deep Learning Algorithm Intern (Autonomous Driving)
Builds
Learning-based driving algorithms, data workflows, and evaluation pipelines for autonomous vehicles
Domain
Autonomous Driving / Deep Learning
Deliverable
production ML models
Required skills
Python, PyTorch, Deep Learning, Transformer architectures, Reinforcement Learning, Supervised Fine-Tuning, Data Analysis, Scenario Mining, Model Evaluation
Preferred skills
VLMs, VLAs, Multimodal Foundation Models, C++, Imitation Learning, Behavior Cloning, Simulation, Open-source contributions
Responsibilities
Develop and evaluate learning-based algorithms for driving decision-making and planning; Build data workflows for scenario mining, cleaning, and labeling; Analyze model failures and vehicle logs to improve dataset balance; Conduct experiments using simulation and vehicle-test results; Support model adaptation across multiple autonomous driving programs