2027 Summer Intern, Data Scaling, Embodied AI (Masters)
Core
Build data pipelines, curation methods, and distributed training infrastructure to scale high-quality datasets for autonomous driving and Embodied AI models.
Role type
Summer Intern, Data Scaling for Embodied AI
Builds
Data pipelines, labeling workflows, distributed training systems, and experiment infrastructure for autonomous driving
Domain
Autonomous driving, Embodied AI, Data Engineering, Distributed Systems
Deliverable
production ML models
Required skills
Python, data processing, machine learning pipelines, large-scale datasets, quantitative analysis, distributed computing
Preferred skills
PyTorch, TensorFlow, JAX, SQL, data warehouses, C++, multimodal sensor data, foundation models
Technologies
Python, PyTorch, TensorFlow, JAX, SQL, C++, distributed training frameworks, cloud infrastructure
Responsibilities
Develop data pipelines for multimodal autonomous driving datasets, analyze data quality and distribution, prototype data mining and labeling approaches, optimize distributed training throughput, build evaluation dashboards, contribute to production software via code reviews and testing
Seniority
Intern, Master's student
