2027 Summer Intern, MS/PhD

Responsibilities

• Own an end-to-end machine learning project from hypothesis formation and dataset construction through model training, evaluation, and results analysis.
• Design experiments measuring how training-data choices such as curation, mining, balancing, and labeling affect perception model quality.
• Build and refine datasets from large-scale camera, lidar, and radar driving data.
• Train and evaluate perception models using Waymo’s existing tooling.
• Develop metrics and analyses to identify model failures and the data needed to address them.
• Share findings with ML engineers and research scientists and help integrate results into production model training.

Requirements

• 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 with JAX, PyTorch, or TensorFlow.
• Hands-on experience with ML data workflows such as dataset building, data curation, labeling, or data quality analysis.
• Strong Python programming skills.
• Ability to design controlled experiments and draw sound conclusions from quantitative results.
• Preferred: end-to-end ML project ownership covering both data and models.
• Preferred: research or industry experience in data-centric ML, including data selection, active learning, data valuation, or curriculum learning.
• Preferred: experience with perception tasks such as 3D detection, tracking, segmentation, or multimodal camera-and-lidar models.
• Preferred: experience processing large datasets with Apache Beam, Spark, or Dataflow.
• Preferred: publications at NeurIPS, ICML, ICLR, CVPR, ICCV, or ECCV venues.

Benefits

• Hybrid onsite internship based at Waymo’s headquarters in Mountain View, California.
• Interns are eligible for the company’s benefits programs, subject to eligibility requirements.
• Applications are accepted on a rolling basis until the role is filled.