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Member of Technical Staff, Foundation Models

Odyssey· Engineering
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Palo Alto, Zurich, LondonFull-timePosted 2mo ago

About the role

Role focused on building and scaling large foundation world models, training from scratch, and advancing state-of-the-art multi-modal, real-time world models at scale across data, architecture, training, inference, and evaluation.

Responsibilities

  • Learn what makes large real-time world models tick. Understand how data, architecture, scale, and diffusion algorithms interact.
  • Run scaling studies and use them: fit scaling laws over model size, data, and compute, and let them pick the next large run rather than intuition alone.
  • Own world model training at scale, large distributed runs across thousands of GPUs, the data mixtures that feed them, and the loss and stability work that keeps them alive for weeks.
  • Implement state of the art ML algorithms, define metrics, and relentlessly iterate on leaderboards.
  • Work end to end across the stack, from data pipelines and tokenizers through training to real-time inference and evaluation.
  • Be part of a team that is defining and leading the world model space.
  • Exploit the latest features on modern GPUs to increase training and inference efficiency.
  • Take ownership of the full ML stack, including the core frameworks that Odyssey researchers and product engineers alike rely on.

Qualifications

  • 2+ years of software engineering experience, with significant work in ML performance.
  • 4+ years of ML engineering experience, or a PhD in a related field.
  • Hands-on experience training large models, pretraining at multi-node scale, and the debugging that comes with it.
  • Comfortable reasoning about scale: scaling laws, compute and data budgets, and what a small-scale ablation does and does not predict.
  • A holistic ML engineer — happy to move between data, model, systems, and evaluation, and to own the whole path from an idea to a shipped model.
  • Track record of owning projects end to end.
  • Not shy to touch any stage of an ML pipeline.
  • Proficiency with PyTorch (or TF/JAX).
  • Highly experiment driven.

Skills

Required:Software EngineeringMachine Learning EngineeringPyTorch (or TF/JAX)End-to-end ML pipeline ownership
Last updated Sep 24, 2026. Interested? Apply on the company site.

About Odyssey

Odyssey is an AI lab focused on general-purpose world models: causal, multimodal systems that learn to predict and interact with the world over long horizons

Odyssey is an AI lab pioneering general-purpose world models—a new form of multimodal intelligence.

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