Member of Technical Staff, Core Model Engineering

Odyssey; Palo Alto, Northern (CA, KY); Hybrid; USD 180,000 - 320,000; Full time

Job summary

Odyssey in Palo Alto seeks an ambitious ML engineer to help build large foundation world models, spanning data pipelines, training at scale, and real-time inference. You will own a unified system, data, architecture, training, inference, and evaluation, pushing the limits of current capabilities.

The role requires hands-on experience training large models, multi-node scaling, and proficiency with PyTorch (or TF/JAX).

Qualifications

• 2+ years of software engineering experience with ML performance.
• 4+ years of ML engineering experience, or a PhD in a related field.
• Hands-on experience training large models at multi-node scale.
• Proficiency with PyTorch (or TF/JAX).
• Holistic ML engineer, owning end-to-end pipelines from data to deployment.

Responsibilities

• Learn what makes large real-time world models tick.
• Run scaling studies and apply scaling laws to guide experiments.
• Own world model training at scale across thousands of GPUs.
• Implement state-of-the-art ML algorithms, define metrics, iterate on leaderboards.
• Work end to end across data pipelines, training, inference, and evaluation.
• Be part of a team shaping the world model space.
• Exploit latest GPU features to boost training and inference efficiency.
• Take ownership of the full ML stack and core frameworks.

Skills

Software engineering

ML performance

Distributed training

PyTorch

Experimentation

Education

MS/PhD in ML/CS

Tools

PyTorch

TensorFlow/JAX

Job description

Who we are

Odyssey is an AI lab pioneering general world models: causal, multimodal systems that learn to predict and interact with the world over long horizons. This foundational technology promises to revolutionize robotics, science, healthcare, education, gaming, defense, and beyond.

Odyssey’s founders previously pioneered the most complex application of physical AI: self-driving cars. They’ve now brought together a world-class research team from DeepMind, Tesla, Waymo, Meta, Apple, and Wayve, who have made significant contributions to language models (DeepMind Gemini), video models (DeepMind Veo), world models (Wayve GAIA), and autonomous systems (Tesla FSD).

Odyssey has raised significant venture capital from GV, Amazon, AMD, EQT, NVIDIA, Natural Capital, In-Q-Tel, Elad Gil, Jeff Dean, Guillermo Rauch, Garry Tan, Kyle Vogt, and researchers from OpenAI, DeepMind, MSL, Recursive, and Thinking Machines.

What we're looking for

The right person will have a deep interest in building large foundation world models, and in the scaling laws that tell you which ones are worth building. You will want to train them from scratch, at the scale that takes: runs across thousands of GPUs, data mixtures measured in years of video, and an interactive model at the end that has to hold up frame by frame under a human's hands. You will treat that as one system, data, architecture, training, inference, evaluation, rather than as six specialties, and go wherever the bottleneck is. This is a cutting edge research area that is not yet mature, so you will be working at the cusp of what’s possible. Most new experiments in this area will fail, your focus will be on maximally learning from failed experiments to increase the chances of eventual success.

What you’ll do

• 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.

Who you are

• 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.