Backed by Initial Capital.
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.
What they'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
More about this role
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...
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