Senior World Models ML Engineer — Onsite SF, Equity & PTO

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

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Equity

401(k)

Paid time off

Parental leave

Commuter benefits

Team lunch

Job summary

Atoms in San Francisco is seeking a Senior Staff Machine Learning Engineer specializing in World Models to help lead the AI organization. You will develop models that learn rich representations of the physical world from large-scale multimodal data, enabling machines to understand environments, predict changes, and support downstream reasoning and action.

Working at the intersection of foundation models, multimodal learning, computer vision, robotics, and embodied AI, you will shape what these

Qualifications

• 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 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 data-architecture-compute-performance relationship.
• Strong understanding of the ML lifecycle from data strategy to inference.
• Experience translating research ideas into functioning ML systems.
• Strong software engineering fundamentals and hands-on Python in ML frameworks.
• Ability to operate in ambiguous research spaces where the architecture may not yet be known.
• Track record of making consequential technical decisions and influencing direction.
• Ability to communicate complex research ideas clearly across disciplines.

Responsibilities

• Define and build architectural foundations for world models and foundation models for physical AI.
• Develop large-scale models that learn representations of complex environments.
• Build models learning from multimodal inputs including video, images, sensor data, and robot state.
• Explore architectures capturing spatial, temporal, semantic, and physical relationships.
• Develop approaches for learning environmental evolution and action effects.
• Research self-supervised, generative, predictive, and representation-learning methods.
• Apply foundation model architectures to robotics and autonomous systems.
• Create training strategies for large real-world and simulated datasets.
• Make architectural decisions spanning data, model design, training, evaluation, and deployment.
• Establish evaluation methodologies for model understanding and prediction.

Skills

ML fundamentals

Foundation models

Multimodal learning

Video models

Self-supervised learning

Embodied AI

Python proficiency

System design

Research leadership

Communication

Tools

Python

Job description

Atoms in San Francisco is seeking a Senior Staff Machine Learning Engineer specializing in World Models to help lead the AI organization. You will develop models that learn rich representations of the physical world from large-scale multimodal data, enabling machines to understand environments, predict changes, and support downstream reasoning and action.

Working at the intersection of foundation models, multimodal learning, computer vision, robotics, and embodied AI, you will shape what these