2027 Summer Intern, PhD, Machine Learning, Computer Vision
Summary
A summer 2027 PhD internship at Waymo in Mountain View focused on machine learning for computer vision in autonomous driving. The intern will analyze and fine-tune multimodal perception foundation models, validate performance on large-scale AV sensor datasets and simulation, and improve data pipelines using tools like PyTorch, JAX, or TensorFlow.
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states.
Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you’re a software engineer or researcher who’s curious and passionate about Level 4 autonomous driving, we'd like to meet you.
Waymo interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!
You will:
- Analyze and characterize internal feature representations of deep multimodal perception foundation models.
- Validate model performance on large-scale autonomous vehicle sensor datasets and simulation environments.
- Train, fine-tune, and evaluate deep neural networks to improve model performance.
- Inspect perception foundational model to derive signal on data quality.
- Implement or augment data pipeline to improve data quality.
You have:
- Currently enrolled in a PhD program in Computer Science, Robotics, Electrical Engineering, or a related quantitative field.
- Experience programming in Python.
- Practical experience training, fine-tuning, and evaluating deep learning models for computer vision or multimodal perception (e.g., using PyTorch, JAX, or TensorFlow).
- Solid understanding of modern neural architectures (e.g., Vision Transformers, multi modal sensor encoders).
We prefer:
- Research experience or publications in multimodal deep learning models, or vision foundational models.
- Hands-on experience working with multi-camera and/or 3D LiDAR perception systems in robotics or autonomous driving.
- Experience evaluating large-scale perception systems under practical settings.
Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.
Skills
As published by greenhouse · 12 questions
Basics
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