2027 Summer Intern, MS/PhD, Perception, Model Lifecycle

The Perception team builds the system which learns the spatial-temporal representation and their semantic meanings of the surrounding environment of the self-driving car, i.e., the system that “perceives” the world around the car. We work jointly with downstream teams on the optimization and integration into the Waymo Driver. We conduct our own research to address real-world problems and collaborate with research teams at Alphabet.  We have access to millions of miles of driving data from a diverse set of sensors, enabling engineers like you to (1) develop methods for efficiently and continuously learning from large scale real-world data, to (2) develop models and model training at scale, to (3) analyze real-world behavior and develop systems for handling the complexities of interacting with the real-world, and (4) optimize models for our onboard and offboard hardware. 

The core challenge within Model Lifecycle is accelerating Waymo's ML development cycle. As we scale to new cities and vehicle platforms, our data volume is exploding, and our models are becoming more complex, handling more and more tasks. This team is critical to controlling that complexity.

Waymo interns work with leaders in the industry on projects that deliver significant impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skillset. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!

This internship will be based on-site at our headquarters in Mountain View, CA.

You Will:

• Own an end-to-end ML project: form a hypothesis, build the dataset, train and evaluate models, and analyze the results.
• Design and run experiments that measure how training data choices (curation, mining, balancing, labeling) affect Perception model quality.
• Build and refine datasets from large-scale multi-sensor driving data (camera, lidar, radar).
• Train and evaluate Perception models with Waymo's existing training and evaluation tooling.
• Develop metrics and analyses that explain where models fail and which data would fix those failures.
• Share findings with ML engineers and research scientists, and help land the results in production model training.

You Have:

• Currently enrolled in an MS or PhD program in Computer Science, Machine Learning, Robotics, or a related field.
• Hands-on experience training and evaluating deep learning models in JAX, PyTorch, or TensorFlow.
• Hands-on experience with the data side of ML, such as building datasets, data curation, labeling, or data quality analysis.
• Strong programming skills in Python.
• Ability to design controlled experiments and draw sound conclusions from quantitative results.

We Prefer:

• Experience on an end-to-end ML project where you owned both the data and the model.
• Research or industry experience in data-centric ML, such as data selection, active learning, data valuation, or curriculum learning.
• Experience with perception tasks such as 3D detection, tracking, segmentation, or multimodal (camera and lidar) models.
• Experience processing large datasets with distributed tools such as Apache Beam, Spark, or Dataflow.
• Publications at ML or computer vision venues (NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV).
• Passion for data-centric AI and autonomous driving.

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.