Machine Learning Engineer: Imitation and Reinforcement Learning for Robotics

We're looking for a Machine Learning Engineer with a focus on behavior learning, specifically data-driven behavior policies and robust data infrastructure. In this role, you'll be responsible for developing and scaling state-of-the-art learning architectures, while also building the data systems that make these models reliable, scalable, and reproducible in production.

- Design, train, validate, and launch models for behavior cloning and reinforcement learning

- Build and maintain data ingestion, labeling, and management pipelines to ensure high-quality training datasets

- Build metrics to evaluate model performance in open loop, simulation, and in the real world

- Collaborate with simulation, systems, and infrastructure teams to integrate ML models into real-world autonomous systems

- Deploy and debug these models in real-world environments, addressing practical issues such as latency, hardware constraints, and system integration

- 3+ years of practical experience applying Machine Learning with Deep Learning frameworks, such as PyTorch/Tensorflow/JAX to solve real-world problems

- 3+ years of professional experience building, deploying, and maintaining Machine Learning models in production environments

- Familiarity with recent literature and methods in learned behavior policies

- Practical experience in behavior cloning and/or reinforcement learning

- Bonus: Experience with diffusion policies, Vision-Language-Action (VLA) models, or related technologies

- Bonus: Published work in conferences such as ICRA, IROS, CoRL, CVPR, ECCV, ICCV, ICML, NeurIPS, ...