Senior Staff ML Engineer: Action Models for Robotic AI

Engg; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Atoms is building AI-powered robotic systems for the real world, combining ML, robotics, and embedded systems. You will help design and implement action models and decision-making architectures for intelligent machines operating in complex environments.

You will work across perception, world models, and ML infrastructure, driving research direction and hands-on engineering in a highly collaborative setting.

Qualifications

• Deep expertise in ML for decision-making, robotics or embodied intelligence.
• Strong understanding of modern deep learning architectures and sequential decision-making.
• Experience with RL, imitation learning, planning, control, or embodied AI.
• Experience linking learned representations to downstream actions.
• Hands-on in Python and/or C++.

Responsibilities

• Define and help build Atoms' architecture for action models and learned decision-making systems.
• Develop models translating learned representations into decisions, plans, and actions.
• Explore architectures for reasoning, planning, control, and action generation.
• Develop policies suitable for real-world robotics and autonomous systems.
• Connect perception and world models to decision-making and control.
• Research imitation learning, reinforcement learning, and behavior learning approaches.
• Train and evaluate models on real-world, simulated, and synthetic data.
• Provide technical leadership through architecture reviews and mentorship.

Skills

Machine learning

Decision-making models

Robotics

Autonomous systems

Embodied intelligence

Python

C++

Deep learning architectures

Sequential modeling

Tools

Python

C++

Job description

Atoms is building AI-powered robotic systems for the real world, combining ML, robotics, and embedded systems. You will help design and implement action models and decision-making architectures for intelligent machines operating in complex environments.

You will work across perception, world models, and ML infrastructure, driving research direction and hands-on engineering in a highly collaborative setting.