Machine Learning Engineer: Imitation and Reinforcement Learning for Robotics
Hybrid (San Francisco, CA)Full-timePosted 3mo ago
About the role
Machine Learning Engineer focused on behavior learning, data-driven behavior policies, and robust data infrastructure to support production-scale learning architectures for autonomous robotics in construction.
Responsibilities
- 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
Qualifications
- 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, …
Last updated Sep 10, 2026. Interested? Apply on the company site.
About Bedrock Robotics
Advanced Autonomy for the Built World
Advanced Autonomy for the Built World
AutonomyBedrock Operatorautonomyheavy machineryindustrial automationindustrial roboticsmachine intelligenceon-site autonomy
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