Staff Machine Learning Engineer - World Models City
About this role
Engineers who thrive in ambiguous research environments and enjoy shaping foundational architectures for physical AI will find a strong fit at Atoms. The team designs real-world robots for industries such as food, mining, and transport, bringing intelligence and efficiency to physical operations. This foundational technical leader will build models that learn rich representations of the physical world from large-scale multimodal data.
Working at the intersection of foundation models, computer vision, robotics, and embodied AI, the person in this role will guide how machines understand and interact with dynamic environments. The position exists to transition theoretical research into scalable production systems deployed on physical hardware. Ideal candidates bring deep machine learning expertise, strong software engineering fundamentals, and a desire to tackle complex real-world challenges.
What you will do
- Define and build the technical architecture for world models and foundation models dedicated to physical AI.
- Develop large-scale models capable of learning from diverse multimodal inputs like video, spatial information, and robot state data.
- Research and apply self-supervised, generative, and predictive approaches for physical world intelligence.
- Establish rigorous evaluation methodologies to measure a model's ability to represent and predict physical environments.
- Partner with cross-functional teams spanning perception, action models, robotics, and ML infrastructure.
- Provide technical leadership through architecture reviews, mentorship, and hands-on Python engineering.
What you need
- Deep expertise in machine learning with hands-on experience building large-scale deep learning or foundation model systems.
- Strong understanding of modern model architectures, representation learning, and the full machine learning lifecycle.
- Practical background in areas such as multimodal learning, video models, generative models, or spatial intelligence.
- Experience training models on large datasets while balancing data, architecture, compute, and performance.
- Demonstrated ability to operate independently in ambiguous research spaces and influence long-term technical direction.
- Solid software engineering fundamentals with proficiency in Python and modern machine learning frameworks.
Benefits
- Medical, Dental, Vision, Disability, and Life Insurance
- Flexible Spending Account / Health Savings Account Options
- 401(k) and equity awards
- Unlimited Flexible Time Off, sick time, paid holidays, and paid parental leave
- Pre-Tax Commuter Benefit Plan
- Team lunch in the SoMa office every Tuesday and Thursday
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
This role is based in the San Francisco office. All office-based teams work onsite, five days a week.
What is the salary range for this role?
The base salary range for this role is $273,000 to $321,000 per year. Actual compensation is determined on an individual basis and may vary depending on experience, skills, and qualifications.
What kind of data will these models process?
Models will learn from multimodal inputs including video, images, spatial information, sensor data, robot state, and other real-world signals.
The application is on the official ATOMS Careers page careers page.
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