2027 Summer Intern, MS/PhD, ML Systems & Behavior Discovery

You will:

• Develop and scale ML pipelines to process telemetry data to discover rare driving interactions
• Benchmark and validate candidate findings to separate meaningful patterns from noise
• Integrate pipelines to turn discovered patterns into concrete, testable artifacts to verify system improvements

You have:

• Currently pursuing graduate degree (Master's or PhD) in Computer Science, Software Engineering or a related technical field
• Strong software engineering skills in Python and/or C++, with experience writing clean, maintainable, and well-tested code
• Demonstrated experience building and operating data or ML pipelines on large-scale datasets (beyond single-machine or notebook prototypes)
• Solid foundational understanding of applied machine learning, statistics, and evaluation methodology (e.g., clustering, anomaly detection, ranking, or metric design)

We prefer:

• Experience working with distributed compute systems, data processing frameworks, or large-scale data lakes (e.g., Apache Spark, Beam/Dataflow, Ray, or internal equivalents)
• Experience with unsupervised learning, outlier/anomaly detection, multimodal embeddings, or LLM/VLM-based evaluation and data filtering
• Track record of taking ambiguous, open-ended problem statements and turning them into practical, working software systems
• Prior research or project experience in autonomous driving, robotics, or spatial-temporal data analysis