AI Researcher (AV) - Internship

Описание

This three-month internship for an AI/ML Research Intern involves working on cutting-edge projects advancing vehicle autonomy and developing algorithms and models for self-driving technology.

Responsibilities

• Lead research and prototyping of advanced machine learning methods, such as foundation models, vision-language architectures, diffusion models, image/video generation, self-supervised learning, imitation learning, and reinforcement learning
• Prototype ML models that improve perception, prediction, or decision-making for autonomous driving
• Collaborate with cross-functional teams, including perception, robotics, and systems engineering
• Participate in technical discussions, share insights, and work towards publishing results

Requirements

• Currently pursuing or in the process of obtaining a Ph.D. in Machine Learning, Artificial Intelligence, Computer Science, or a related technical field
• Able to work fulltime during the academic summer break
• 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

Nice to have

• Intent to return to degree program after the completion of the internship
• Familiarity with autonomous vehicles or advanced driver assistance systems (ADAS)
• Experience working with large-scale datasets and training ML models in high-performance computing environments
• 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
• Experience building systems based on machine learning, reinforcement learning and/or deep learning methods

We offer

• This position is limited to the three-month
• Students are expected to work full-time in a hybrid setup, including at least three onsite days per week