2027 Summer Intern, PhD, Machine Learning, Computer Vision

Location: Mountain View, California

Department: Pipeline (N/A)

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.
• Design and implement active learning and intelligent data curation algorithms to identify rare, safety-critical edge cases.
• Explore automated data labeling and validation workflows leveraging modern Vision-Language Models (VLMs).
• Train, fine-tune, and evaluate deep neural networks to improve model performance.
• Validate model performance on large-scale autonomous vehicle sensor datasets and simulation environments.

You have:

• Currently enrolled in a PhD program in Computer Science, Robotics, Electrical Engineering, or a related quantitative field.
• Experience programming in Python and C++.
• 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 active learning, self-supervised representation learning, core-set selection, or multi modal foundation models (VLMs).
• Hands-on experience working with multi-camera or 3D LiDAR perception systems in robotics or autonomous driving.
• Experience building VLM evaluation/judge pipelines or large-scale data mining workflows.
• Familiarity with high-dimensional feature analysis and clustering techniques.

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.