Staff Robot Learning Engineer: Real-World Manipulation

present of AI; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Darwin develops general-purpose humanoid robots designed to learn physical manipulation tasks through real-world experience. The role focuses on building models and policies that let robots learn from demonstrations and real-world data, balancing research with deployment.

The candidate should bring deep learning foundations and a strong ML background, with a passion for experiments, data-driven evaluation, and applying ideas to real hardware. This is an on-site position in San Francisco.

Qualifications

• Strong machine learning foundations and depth in at least one ML area.
• Careful thinking about experiments and data.
• Drive to carry ideas from research through deployment.

Responsibilities

• Build models and policies that enable humanoid robots to learn physical tasks from demonstrations and real-world experience.
• Develop data collection and training pipelines for robot learning.
• Test and validate policies on actual robots with dexterous manipulation tasks.
• Explore new learning architectures and evaluate performance in real hardware environments.

Skills

Deep learning foundations

Manipulation learning

Job description

Darwin develops general-purpose humanoid robots designed to learn physical manipulation tasks through real-world experience. The role focuses on building models and policies that let robots learn from demonstrations and real-world data, balancing research with deployment.

The candidate should bring deep learning foundations and a strong ML background, with a passion for experiments, data-driven evaluation, and applying ideas to real hardware. This is an on-site position in San Francisco.