Behavior ML Engineer Intern: Learned Manipulation Policies

We Love AI Jobs; San Francisco (CA); Presencial; USD 34 000 - 55 000; Tempo integral

Resumo da oferta

Bedrock Robotics in San Francisco offers an on-site internship in Behavior ML focused on training learned policies for autonomous excavators using real demonstrations and simulations. You’ll contribute to the team’s training codebase and help evaluate policy performance across tasks like juggling safety and efficiency.

Ideal candidates are pursuing BS/MS/PhD in CS/robotics/ML, with strong Python and PyTorch experience, and familiarity with diffusion models, flow matching, VAEs, or imitation

Qualificações

• Currently pursuing BS, MS, or PhD in CS/robotics/ML or equivalent
• Strong Python and PyTorch experience training models
• Experience with diffusion models, flow matching, VAEs, or imitation learning
• Experience running training experiments and distinguishing real improvements from noise
• Good communication of results and next steps

Responsabilidades

• Train and iterate on diffusion flow matching, and related behavior policies using real fleet demonstration data and simulated rollouts
• Run architecture, conditioning, and hyperparameter explorations, and turn results into clear findings
• Build and improve evaluation pipelines that score behavior models on task success, smoothness, safety margins, and operator-likeness
• Investigate failure modes - distribution shift, mode collapse, out-of-distribution scenes and propose fixes
• Work with the simulation and eval teams to ensure offline metrics predict on-machine performance
• Contribute to the shared training codebase with clean, reproducible work
• Share results regularly with the behavior, controls, and autonomy teams

Conhecimentos

Python

PyTorch

diffusion models

flow matching

imitation learning

behavior cloning

model evaluation

robot manipulation

Formação académica

BS/MS/PhD in CS/Robotics/ML (in progress)

Descrição da oferta de emprego

Bedrock Robotics in San Francisco offers an on-site internship in Behavior ML focused on training learned policies for autonomous excavators using real demonstrations and simulations. You’ll contribute to the team’s training codebase and help evaluate policy performance across tasks like juggling safety and efficiency.

Ideal candidates are pursuing BS/MS/PhD in CS/robotics/ML, with strong Python and PyTorch experience, and familiarity with diffusion models, flow matching, VAEs, or imitation