Member of Technical Staff, Diffusion World Models & Robotics

Odyssey; Zürich; Vor Ort; CHF 120.000 - 180.000; Vollzeit

Zusammenfassung

Odyssey is an AI lab pioneering general world models for robotics and beyond. We seek researchers and engineers with deep ML curiosity who can push diffusion-based world models toward real hardware deployments.

You will work at the intersection of diffusion, world models, and model-based RL, building pipelines, experiments, and policy integrations for cutting-edge robotic systems. Zurich in person work is common and collaboration is global.

Qualifikationen

• PhD or equivalent research experience is required or strongly preferred.
• Hands-on experience with diffusion/world models or model-based RL is essential.
• Proven ability to own projects end-to-end and work across ML pipelines.

Aufgaben

• Learn how interactive world models integrate data, diffusion backbones, action conditioning and downstream policies.
• Implement state-of-the-art diffusion and robot-learning algorithms, design losses and RL objectives.
• Run rapid ablations across world models and policies, explore architectures and data mixes.
• Bridge to real robots through data pipelines, fine-tuning and deployment on Robot as a Service platforms.
• Utilize GPUs to improve training and inference efficiency.
• Take ownership of the full ML stack used by Odyssey researchers and product engineers.

Kenntnisse

PyTorch

Diffusion models

World models

Model-based RL

Experiment-driven

Data pipelines

Ausbildung

PhD or equivalent research experience

Tools

Python

TensorFlow/JAX

Jobbeschreibung

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.