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Staff Machine Learning Engineer - World Models City

Join Atoms as a Staff Machine Learning Engineer to develop AI systems that understand and predict the physical world.

Location
San Francisco, CA
Compensation
$273k–$321k/yr
Level
staff
Type
full time · On-site

Posted by employer 2 days ago

First seen on Joblaze 2 days ago

Last verified on the company career page 3 hours ago

Apply at Atoms → Save job Scanned from atoms.co

What you'll build

  • Define technical architecture for world models
  • Develop large scale models for physical environments
  • Build models from multimodal inputs
  • Establish evaluation methodologies for models
  • Translate research into operational systems

Must have

  • Deep expertise in machine learning
  • Experience developing large-scale deep learning systems
  • Strong understanding of modern model architectures
  • Experience training models on large-scale datasets
  • Strong software engineering fundamentals

Nice to have

  • Experience with multimodal learning
  • Experience with generative models
  • Experience with self-supervised learning
  • Experience with predictive models
  • Experience with spatial intelligence

Practical constraints

  • Onsite, five days a week

Not disclosed in this posting: years of experience, visa sponsorship.

Benefits

401k Match Unlimited PTO Equity/Stock Options Health Insurance Parental Leave

Joblaze summary

In the role of Staff Machine Learning Engineer at Atoms, the individual will focus on developing advanced models that enable machines to understand and predict complex physical environments using multimodal data. Key skills include expertise in large-scale deep learning, foundation models, and a strong grasp of the machine learning lifecycle, particularly in areas like generative and self-supervised learning. This position is suited for a senior-level engineer with a proven track record in translating research into practical applications and making impactful technical decisions. Atoms emphasizes collaboration and innovation, positioning itself at the forefront of integrating AI into real-wor

Joblaze insights

  • Listed 2 days ago — first seen on Joblaze September 25, 2026. Last confirmed on Atoms's careers page September 27, 2026.
  • Salary band is above the typical range for AI/ML roles (median ~$190,000).
  • Starts above 88% of 33 comparable staff ai/ml roles in United States that list Machine Learning we track (median $222,716 across 14 companies). See Machine Learning salary trends
  • Machine Learning appears in 17.3% of 255 comparable staff ai/ml roles in United States; Robotics appears in 0.4% of 255 comparable staff ai/ml roles in United States.

Quick facts

Is the Staff Machine Learning Engineer - World Models City role remote?
No — this is an on-site role in San Francisco, CA.
What's the salary range?
Atoms lists $273,000–$321,000 for this role.
Where is the role based?
Atoms is hiring for this position in San Francisco, CA.
What's the tech stack?
Joblaze extracted these technologies from the posting: Computer Vision, Deep Learning, Embodied AI, Foundation Models, Machine Learning, Robotics.
What seniority level is this role?
Atoms targets staff-level candidates for this position.
Is this full-time or contract?
Full-time for this Staff Machine Learning Engineer - World Models City role at Atoms.

From the original posting

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 World Models, you will be one of the foundational technical leaders of Atoms' AI organization. You will help develop models that learn rich representations of the physical world from large scale multimodal data enabling machines to understand environments, model how those environments evolve, and provide the learned representations needed for downstream reasoning and action. This is an opportunity to help define a new generation of physical AI systems.

Rather than relying exclusively on traditional, independently engineered perception and autonomy components, we are exploring foundation model approaches capable of learning from diverse sensor inputs and large amounts of real world experience. You will work at the intersection of foundation models, multimodal learning, computer vision, robotics, and embodied AI to help determine what these systems should look like at Atoms.

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

What you'll do

  • Define and help build Atoms' technical architecture for world models and foundation models for physical AI.
  • Develop large scale models that learn representations of complex, dynamic physical environments.
  • Build models capable of learning from multimodal inputs including video, images, spatial information, sensor data, robot state, and other realworld signals.
  • Explore architectures that capture spatial, temporal, semantic, and physical relationships within realworld environments.
  • Develop approaches for learning how environments evolve over time and how actions influence future states.
  • Research and build self supervised, generative, predictive, and representation earning approaches for physical world intelligence.
  • Explore the application of modern foundation model architectures to robotics and autonomous systems.
  • Develop training strategies that take advantage of largescale realworld and simulated datasets.
  • Make architectural decisions spanning data, model design, pretraining, finetuning, evaluation, inference, and deployment.
  • Establish evaluation methodologies for measuring a model's ability to understand, represent, and predict the physical world.
  • Partner closely with engineers and researchers working across perception, action models, robotics, autonomy, simulation, and ML infrastructure.
  • Translate emerging research into systems capable of operating on real machines in real environments.
  • Provide technical leadership through research direction, architecture reviews, mentorship, experimentation, and handson 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 large-scale deep learning or foundation model systems.
  • Strong understanding of modern model architectures and representation learning.
  • Experience with one or more areas such as multimodal learning, video models, generative models, self-supervised learning, predictive models, spatial intelligence, or embodied AI.
  • Experience training models on large-scale datasets and understanding the relationship between data, architecture, compute, and model performance.
  • 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 handson in Python and modern ML frameworks.
  • 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.

Why join us

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 Francisco office. 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.

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
  • Paid Parental Leave
  • Pre-Tax Commuter Benefit Plan
  • Team lunch in our SoMa office every Tuesday and Thursday

#LI-Onsite

Standard company text repeated across Atoms's postings is omitted here.

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