Human Interactive Driving Research Intern, World Models

What you'll do

• Research world modeling, multi-agent interaction, reinforcement learning, perception, or sim-to-real transfer; design, train, and evaluate driving systems with researchers.
• Develop and evaluate prototypes in closed-loop simulations and, time permitting, on autonomous driving hardware; work with large-scale datasets.
• Present findings internally and work toward a top-tier academic publication.

What they ask for

• Currently pursuing a Ph.D. in Computer Science, Robotics, Machine Learning, Electrical Engineering, or a related field.
• Strong machine learning background, particularly in deep learning, generative models, reinforcement learning, or probabilistic modeling.
• Hands-on experience with world models, model-based reinforcement learning, 3D reconstruction or sensor fusion, and large-scale simulation for robotics or autonomous systems.
• Proficient coding skills and expertise in modern deep learning frameworks; prior publication(s) in top-tier AI/ML conferences.

Nice to have

• Experience with autonomous driving datasets or open-source foundation models.
• Experience with Amazon Web Services (e.g., S3, EC2, SageMaker).

Pay

$45 and $65/hour (USD, base pay)

Tools

PyTorch, JAX, TensorFlow, Amazon Web Services, S3, EC2, SageMaker

AI focus

Research and develop world models and learning-based autonomous driving systems, including representation learning, action conditioning, multi-agent interaction, and evaluation.