Staff Machine Learning Engineer - Action Models

Atoms; San Francisco (CA); On-site; USD 273,000 - 321,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401(k)

Equity

Sick Time and Paid Holidays

Team lunch

Job summary

Atoms is pioneering Physical AI, building real-world robotics to move industries like food and mining. As a Senior Staff Machine Learning Engineer focused on Action Models, you’ll lead architecture and modeling at the intersection of ML, robotics, and embodied AI.

Your work will enable machines to reason about their environment, make decisions, and act in physical settings. The role sits in SF, onsite, with a base salary range of $273,000 - $321,000 per year.

Qualifications

• Expertise in ML for decision-making and embodied AI.
• Strong DL architectures for sequential decision-making.
• Experience in RL, imitation learning, planning or robot learning.
• Systems connecting representations to actions.
• Experience training on large-scale real-world, simulated, or synthetic data.
• Full ML lifecycle understanding from data strategy to inference.
• Translate research ideas into functioning ML systems.
• Hands-on in Python and/or C++.

Responsibilities

• Define and build architecture for action models and learned decision-making.
• Develop models translating learned representations into decisions, plans, and actions.
• Explore reasoning, planning, control, and action generation in complex environments.
• Develop learned policies for real-world robotics and autonomous systems.
• Connect perception and world models to downstream decision-making and control.
• Research imitation learning, reinforcement learning, behavior learning, and data-driven decision-making.
• Explore multimodal architectures for physical AI.
• Train and evaluate models using real and simulated data.
• Learn from demonstrations, human behavior, robot experience.

Skills

ML for decision-making

Robotics/embodied AI

Deep learning architectures

Temporal modeling

Sequential decision-making

Python/C++

Research-to-implementation

Cross-disciplinary communication

Tools

Python

C++

Job description

Who we are

Atoms is building the machines that power the next era of progress.

Over the last decade, software has transformed the digital world. But the physical world, where food is made, minerals are mined, goods are moved, and industries are run, remains far less intelligent, far less efficient, and far more constrained. We’re changing that.

Atoms builds Physical AI— real-world robots for the industries that move civilization forward, starting with food, mining, and transport. Our systems are designed to understand, predict, and control the real world with precision, turning complex physical operations into something more reliable, more scalable, and more productive.

This work requires more than robotics. It requires deep integration across hardware, software, AI, operations, manufacturing, and real estate. We don’t just build machines in a lab. We deploy them into real environments, operate them, learn from them, and improve them until they work at scale.

We are roboticists, engineers, operators, and builders. We believe the next great technology companies will not only transform information, but the physical systems that shape everyday life.

If you want to work on hard problems with real‑world impact, join us.

About the role

As a Senior Staff Machine Learning Engineer focused on Action Models, you will be one of the foundational technical leaders of Atoms' AI organization. You will help develop models that enable intelligent machines to reason about their environment, make decisions, and translate those decisions into actions in the physical world. This role sits at the intersection of machine learning, robotics, autonomous systems, planning, and embodied AI.

You will explore how modern foundation models, world models, and learned representations can be connected to action moving beyond systems built entirely from independently engineered components toward models capable of learning increasingly sophisticated behaviors from data and experience.

The problems are open-ended, the architecture is still being defined, and the systems you build will ultimately need to work outside of a research environment on real machines operating in complex physical environments.

This is a deeply technical individual contributor role with significant influence over Atoms' research direction and long-term AI architecture.

What you'll do

• Define and help build Atoms' technical architecture for action models and learned decision‑making systems.
• Develop models that translate learned representations of the physical world into decisions, plans, and actions.
• Explore architectures for reasoning, planning, control, and action generation within complex physical environments.
• Develop learned policies and action heads capable of operating across real-world robotics and autonomous systems.
• Explore approaches that connect perception and world models directly to downstream decision‑making and control.
• Research and develop techniques across imitation learning, reinforcement learning, behavior learning, and other data‑driven approaches to decision‑making.
• Explore vision‑language‑action and other multimodal architectures for physical AI.
• Develop approaches that allow models to reason across temporal horizons and understand how actions influence future states.
• Train and evaluate models using large‑scale real‑world, simulated, and synthetic data.
• Develop methods for learning from demonstrations, human behavior, robot experience, and other sources of supervision.
• Make architectural decisions spanning data, model design, training, evaluation, inference, and deployment.
• Establish evaluation methodologies for measuring reasoning, planning, action quality, robustness, and generalization.
• Partner closely with researchers and engineers working across perception, world models, robotics, autonomy, simulation, and ML infrastructure.
• Translate emerging research in embodied intelligence into systems capable of operating reliably on real machines.
• Provide technical leadership through research direction, architecture reviews, mentorship, experimentation, and hands‑on engineering.
• Help establish the technical bar for the growing AI Research organization and participate in identifying and assessing exceptional engineering and research talent.

What we're looking for

• Deep expertise in machine learning with experience developing models for decision‑making, robotics, autonomous systems, or embodied intelligence.
• Strong understanding of modern deep learning architectures and their application to sequential decision‑making and physical systems.
• Experience with one or more areas such as reinforcement learning, imitation learning, behavior learning, planning, control, robot learning, or embodied AI.
• Experience developing systems that connect learned representations or perception to downstream actions.
• Strong understanding of sequential and temporal modeling and the relationship between actions and future states.
• Experience training and evaluating models using large‑scale real‑world, simulated, or synthetic datasets.
• Strong understanding of the full ML lifecycle, including data strategy, model architecture, training, evaluation, optimization, and inference.
• Experience translating research ideas into functioning machine learning systems.
• Strong software engineering fundamentals and the ability to remain deeply hands‑on in Python and/or C++.
• Demonstrated ability to operate in ambiguous research spaces where the architecture and solution may not yet be known.
• A track record of making consequential technical decisions and influencing research or engineering direction beyond an individual project.
• Ability to communicate complex research and technical ideas clearly and collaborate across research, engineering, and robotics disciplines.

At Atoms, you’ll work on one of the defining challenges of our time—bringing automation into the physical world to drive real, lasting impact. We exist to uncover valuable unknown truths and turn them into progress, which means constantly pushing beyond what’s known and building what doesn’t yet exist. The work is ambitious and often challenging, but it’s grounded in a shared sense of purpose and a team committed to seeing it through together. Our work only matters if it serves others, and we know that meaningful progress depends on the trust of the people we serve and the strength of our team—so we invest in both, creating an environment where you can do your best work and grow.

What else you need to know

This role is based in our San Franciscooffice. Atoms is a company driven by invention and continuous change - we are constantly reimagining our industries, building new products, and refining how we operate. We do our best work together. That’s why all of our office‑based teams work onsite, five days a week.

The base salary range for this role is $273,000 - $321,000 per year.

Actual compensation will be determined on an individual basis and may vary depending on experience, skills, and qualifications.

Base salary is just one part of your total rewards package. You may also be eligible for equity awards.

Benefits Summary (USA Full-Time Exempt Employees):

• Medical, Dental, Vision, Disability, and Life Insurance
• Flexible Spending Account / Health Savings Account Options
• 401(k)
• Equity
• Sick Time, Unlimited Flexible Time Off, and Paid Holidays
• Team lunch in our SoMa office every Tuesday and Thursday

Benefits are subject to change at the company's discretion.
Atoms accepts applications on an ongoing basis.

Ready to join us as we serve those who serve others?

#LI-Onsite

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