2027 Summer Intern, MS/PhD, Machine Learning Engineer

Highlights

• Train multi-task models over driving-log sequences to improve evaluation quality.
• Run rigorous offline and end-to-end evaluations on real hillclimbing A/B runs.
• Land production-quality code and present results to partner teams.

What they offer

• Housing/relocation bonus (if applicable)
• Medical, dental, and vision insurance
• Free breakfast, lunch, dinner, and snacks
• Free access to Google shuttles
• Onsite gym
• Fun intern events and networking opportunities

Ideal candidate

A curious MS or PhD student passionate about autonomous driving who loves rigorous experimentation and turning real-world data into safer mobility through collaborative, impactful research.

Requirements

• Currently enrolled in MS or PhD program in Computer Science, Machine Learning or related field and returning after internship
• Hands-on experience training and evaluating deep learning models including data pipelines, losses, and debugging training runs
• Strong programming skills in C++/Python with grounding in ML fundamentals including precision/recall, class imbalance and experiment design
• Authorship of published papers in top-tier AI/ML, data mining, or computer vision conferences
• Research or applied experience with transformer and sequence models, multi-task and transfer learning
• Experience with distributed training and large-scale data processing for training and evaluation datasets
• Familiarity with autonomous driving, robotics, simulation, calibration and uncertainty quantification