Member of Technical Staff, Diffusion World Models & Robotics

Odyssey; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

In‑person collaboration

Job summary

Odyssey is an AI lab pursuing general world models for continuous interaction with the real world. We seek researchers who can advance diffusion-based world models and robot-policy training, with hands-on work across data, models, and deployment to real hardware.

The role values experimental rigor and a track record of delivering end-to-end ML projects, including sim-to-real work and scalable training on modern GPUs. In-person collaboration in the global hubs is common.

Qualifications

• A PhD (or equivalent research experience) plus 2+ years of relevant research/engineering experience, or 4+ years software engineering with 2+ years ML work.
• Hands-on experience with diffusion models, world models, model-based RL, or VLA policies.
• Track record of owning projects end to end.
• Comfort across the ML pipeline from data to real-robot deployment; sim-to-real is a plus.
• Proficiency with PyTorch (or TF/JAX).

Responsibilities

• Learn what makes interactive world models tick, including data, diffusion backbones, action conditioning and policies.
• Implement state-of-the-art diffusion and robot-learning algorithms, design losses and RL fine-tuning.
• Run ablations across WM and policy spanning architectures and data mixes.
• Build data pipelines, WM fine-tuning, and policy deployment onto Robots-as-a-Service and partner systems.
• Exploit latest GPU features to increase training and inference efficiency.
• Take ownership of the full ML stack used by Odyssey researchers and product engineers.

Skills

PyTorch

Diffusion models

World models

Model-based RL

Robotics data pipelines

ML research

TF/JAX

Education

PhD or equivalent

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

We are looking for people with a deep interest in improving machine learning algorithms at the intersection of diffusion world models and robotics. Interactive, action‑conditioned world models are a cutting‑edge research area that is not yet mature. You will be working at the cusp of what’s possible, using world models as simulators, feature extractors, and training grounds for real robot policies and model‑based RL approaches. Most new experiments here will fail; your focus will be on maximally learning from failed experiments to increase the chances of eventual success on real hardware.

What You’ll Do

• Learn what makes interactive world models tick. How data, diffusion backbones, action conditioning, and downstream policies interact.
• Implement state‑of‑the‑art diffusion and robot‑learning algorithms, and design losses, reward functions, and reinforcement/preference‑based fine‑tuning for interactivity and policy performance.
• Run a high cadence of ablations across WM and policy, from architecture and feature taps to data mixes and conditioning schemes.
• Build the bridge to real robots: data pipelines, WM fine‑tuning, and policy deployment onto Robots‑aaS and design partner systems (remote and face‑to‑face).
• Exploit the latest features on modern GPUs to increase training and inference efficiency.
• Take ownership of the full ML stack, including core frameworks that Odyssey researchers and product engineers rely on.

Who You Are

• A PhD (or equivalent research experience) plus 2+ years of relevant research or engineering experience, or 4+ years of software engineering experience with 2+ years of relevant ML work.
• Significant hands‑on experience with one or more of: diffusion models, world models, model‑based RL (e.g. Dreamer lineage), or vision‑language‑action (VLA) policies.
• Track record of owning projects end to end.
• Not shy to touch any stage of an ML pipeline, from data to real‑robot deployment; sim‑to‑real experience is a strong plus.
• Proficiency with PyTorch (or TF/JAX).
• Highly experiment‑driven.
• Flexible to work in‑person in Zurich, London, or the Bay Area. Most of the team works in‑person in Zurich at the moment.