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.

What you’ll do:

• 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

What we’re looking for:

• Practical experience applying machine learning with deep learning frameworks, such as PyTorch, to solve real-world problems

• Proficiency in Python and comfort with at least one systems language (e.g., C++, Rust)

• 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, …