Research Engineer, Infrastructure
We are building a general AI for robots that learns in the real world with minimal human supervision. Our robots collect massive amounts of data autonomously containing valuable failures and recoveries while minimizing unscalable human language advice and teleoperation. We develop world-model based reinforcement learning algorithms to learn reliable policies from this dataset and improve beyond human performance.
You might thrive in this role if you enjoy building scalable systems for machine learning and can design infrastructure that enables cutting-edge AI research.
Responsibilities
- Design and implement scalable data collection pipelines from our robot fleet
- Build and maintain distributed training infrastructure for large neural networks
- Optimize model inference speed
Preferred Qualifications
- Strong software engineering skills with experience in Python and distributed systems
- Experience with ML infrastructure, including training pipelines and data management
- Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
- Knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow)
- Experience with high-performance computing and GPU optimization