2027 Summer Intern, PhD, Machine Learning, Simulation Realism

Highlights

• Develop controllable, realistic adversarial agents for simulation evaluation.
• Iterate post-training recipes for state-of-the-art foundation and world models.
• Deploy new agents in the Waymo Simulator for large-scale testing.

Ideal candidate

PhD student in CS, ML, or robotics passionate about autonomous driving simulation. Curious researcher who loves building realistic agents and improving foundation models through experimentation.

Requirements

• Currently pursuing a PhD in Computer Science, Machine Learning, Robotics, or related technical field
• Proficient in Python coding and tensor manipulation (PyTorch / NumPy / JAX / TensorFlow / etc.)
• Experience with machine learning and deep learning
• Hands-on experience with post-training and reinforcement learning (preferred)
• Hands-on experience with attention mechanisms, diffusion and/or autoregressive architectures (preferred)
• Experience with autonomous driving or robotics (preferred)