Robot Learning Engineer — Dexterous Manipulation

Darwin (YC F25)

San Francisco (CA)

On-site

USD 140,000 - 220,000

Full time

48 hours ago
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Job summary

Darwin (YC F25) is building autonomous robots for data centers. We seek a machine learning researcher or engineer who can design and train models, develop policies, and advance learning systems that operate in the physical world.

You will work across research and deployment to enable robots that learn from demonstrations and experience. You should be proficient in Python, PyTorch, and NumPy, with deep learning foundations and a willingness to tackle cross-disciplinary challenges.

Qualifications

  • Expertise in at least one ML subfield with ability to contribute across disciplines.
  • Experience designing and training models and pipelines for real-world data.
  • Ability to reason about architectures, data, experiments, and results.

Responsibilities

  • Robot Learning: research, design, and train models and policies for learning complex physical tasks from demonstrations and experience.
  • Dexterous Manipulation: develop learning approaches for precise manipulation, assembly, and tool use.
  • Learning Architectures: design architectures and algorithms for robot perception, reasoning, and control.
  • Data & Training: design data collection strategies, training pipelines, and methods for learning from real-world data.
  • Evaluation & Deployment: design experiments, evaluate performance, and improve policies on physical robots.

Skills

Deep learning
Python
PyTorch
NumPy

Tools

PyTorch
NumPy

Job description

Darwin (YC F25) is building autonomous robots for data centers. We seek a machine learning researcher or engineer who can design and train models, develop policies, and advance learning systems that operate in the physical world.

You will work across research and deployment to enable robots that learn from demonstrations and experience. You should be proficient in Python, PyTorch, and NumPy, with deep learning foundations and a willingness to tackle cross-disciplinary challenges.

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