Machine Learning Engineer Intern
CloudKitchens5 hours ago
San Francisco, CA, USAIntern
Responsibilities
- Prototype, evaluate, and test machine learning and deep learning models for trajectory planning and autonomous behavior.
- Design and evaluate multimodal systems integrating camera, LiDAR, and radar data for spatial-temporal perception.
- Develop interactive world models and simulation tools to replay driving logs and analyze vehicle trajectories.
- Profile and optimize inference pipelines for low-latency execution on vehicle edge hardware.
- Identify, curate, and structure rare edge cases and long-tail scenarios through data engineering workflows.
- Partner with validation and QA teams to test model releases in simulated scenarios, detect regressions, and track model behavior.
Requirements
- Currently pursuing a BS, MS, or PhD in Computer Science, Robotics, Electrical Engineering, Data Science, or a related technical field.
- Strong foundation in deep learning and experience with PyTorch or JAX through coursework, research, or prior internships.
- Hands-on programming experience in Python; familiarity with C++ is a plus.
- Academic, project, or research experience in computer vision, spatial-temporal modeling, reinforcement learning, model optimization, model evaluation, or data engineering.
- Familiarity with robotics data structures or processing camera, LiDAR, or radar data is highly preferred.
- Interest in solving complex real-world engineering problems and deploying AI into physical systems.
Benefits
- 12-week internship program with Winter 2027 and Summer 2027 cohort options.
- Role is based in the San Francisco office and requires onsite work five days per week.
- Base salary is $70.00 per hour.
Categories
ML EngineeringRobotics
About CloudKitchens
CloudKitchens builds delivery-first commercial kitchen facilities and restaurant software for food and beverage operators. It leases turnkey kitchen space and provides tools for order management, delivery logistics, and multi-brand operations, enabling restaurants and entrepreneurs to expand with lower upfront costs. The company is privately held and headquartered in Los Angeles, serving markets across the U.S. with a mix of owned sites and enterprise solutions.