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

What you'll do

• Build and refine datasets from large-scale camera, lidar, and radar driving data; train and evaluate perception models.
• Design experiments and develop metrics to identify model failures and the data that could address them.
• Analyze results and share findings with ML engineers and research scientists to support production model training.

What they ask for

• 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 ML data work, such as dataset building, data curation, labeling, or data quality analysis.
• Strong Python programming skills and ability to design controlled experiments and draw sound conclusions from quantitative results.

Nice to have

• Experience with end-to-end ML projects, data-centric ML, perception tasks, or large-scale distributed data tools.
• Publications at ML or computer vision venues, or passion for data-centric AI and autonomous driving.

Pay

$70 — $70 USD (base hourly pay, Masters); $85 — $85 USD (base hourly pay, PhD)

Tools

JAX, PyTorch, TensorFlow, Python, Apache Beam, Spark, Dataflow

AI focus

Data-centric perception ML: investigate training-data choices, build datasets, train and evaluate models, and analyze failure patterns for autonomous driving.