Waymo is looking to improve the Waymo Driver, their autonomous driving technology, by developing state-of-the-art simulations for testing and training. This involves creating realistic environments and generating complex scenarios to enhance the performance and safety of the Waymo Driver.
Requirements
- Strong publication record in top-tier AI/ML or VL conferences and demonstrated expertise in AI Architecture, Deep Learning, Reinforcement Learning, High Performance Computing, Compilers, and/or Computer Architecture.
- Hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow, JAX) and ML coding, proficiency in Python and/or C/C++
- Experience with large-scale model training, including large diffusion models, world modeling, foundational models, ML modeling and system design and experience in 3D Vision, including 3D or 4D Gaussian Splatting, 3D Assets Generation, etc.
- Proficiency in ML frameworks like Jax, XLA, and/or TPU, and contributions to relevant open-source projects.
- Demonstrated expertise in research domains such as Deep Learning, Reinforcement Learning, Distributed systems, AI Architecture, and familiarity with 3DGS/NeRF technologies.
Responsibilities
- Research, implement, and evaluate state-of-the-art generative models and advanced sampling techniques for ultra-realistic multi-agent simulations and full fidelity scenario generation.
- Collaborate with research and engineering teams to integrate models into Waymo's simulation and verification workflows, applying cutting-edge VL and ML efficiency technology.
- Contribute to projects that evaluate and improve world modeling of high fidelity sensor data for Waymo's E2E AI-first Driver, with opportunities to publish novel research.
Other
- Currently pursuing a Ph.D. in Computer Science, Machine Learning, Electrical Engineering, or a related technical discipline.
- This internship will be based on-site at our headquarters in Mountain View, CA.
