2027 Summer Intern, MS/PhD

Responsibilities

• Develop and scale ML pipelines for processing telemetry data and discovering rare driving interactions.
• Benchmark and validate candidate findings to separate meaningful patterns from noise.
• Integrate discovered patterns into concrete, testable artifacts that verify system improvements.

Requirements

• Currently pursuing a Master’s or PhD in Computer Science, Software Engineering, or a related technical field.
• Strong software engineering skills in Python and/or C++, including 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.
• Foundational understanding of applied machine learning, statistics, and evaluation methodology, including areas such as clustering, anomaly detection, ranking, or metric design.
• Preferred: experience with distributed compute systems, data processing frameworks, or large-scale data lakes such as Apache Spark, Beam/Dataflow, Ray, or equivalent systems.
• Preferred: experience with unsupervised learning, outlier or anomaly detection, multimodal embeddings, or LLM/VLM-based evaluation and data filtering.
• Preferred: experience turning ambiguous, open-ended problems into practical working software systems.
• Preferred: research or project experience in autonomous driving, robotics, or spatiotemporal data analysis.

Benefits

• Hybrid onsite internship position.
• Competitive compensation package with a housing or relocation bonus if applicable.
• Medical, dental, and vision insurance, subject to eligibility requirements.
• Fun intern events and networking opportunities.
• Onsite meals, snacks, Google shuttles, and gym access if the internship is onsite.
• Applications accepted on a rolling basis until the role is filled.