Applied Deep Learning Algorithm Intern, Autonomous Driving - 2027

Responsibilities

• Develop, train, fine-tune, and evaluate learning-based algorithms for autonomous driving decision-making, planning, and driving behavior.
• Build supervised fine-tuning data workflows and Python tools for scenario mining, data cleaning, filtering, labeling, experiment management, visualization, and model evaluation.
• Analyze model failures and vehicle logs, mine hard cases, and improve dataset balance, long-tail coverage, and noise quality.
• Conduct supervised fine-tuning, reinforcement learning, ablation, and evaluation experiments using offline metrics, open-loop replay, simulation, and vehicle-test results.
• Support model and carline adaptation across multiple autonomous driving programs, including issue analysis, validation, and scaling.

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