9 months ago
Responsibilities
- Own and scale a data platform that ingests large volumes of video streams and makes them available for real-time training.
- Own the end-to-end ML infrastructure stack, including distributed training, experiment tracking, and cluster management.
- Build data management systems and high-performance data access layers for petabyte-scale multimodal data.
- Collaborate with the research team to design and run experiments that improve robotic policy capabilities.
- Maintain high availability and reliability of critical infrastructure.
Requirements
- Deep experience building and operating petabyte-scale data systems, ideally in autonomous vehicles or robotics.
- Experience with real-time processing, streaming, and event-driven systems.
- Experience building deep learning training and inference systems at scale.
- Ability to work autonomously in a high-trust, high-autonomy environment.
- Passion for robotics and physical AI.
- Bonus: experience with large-scale autonomous vehicle or robotics datasets, distributed ML training at scale, video codecs and compression, efficient video storage and retrieval, reinforcement learning, imitation learning, VLA model training pipelines, or production hardware systems.
Benefits
- In-person work at the company's NYC-based location.
- High-trust, high-autonomy environment with significant opportunity for immediate impact and personal growth.
Categories
Data EngineeringML Engineering
