Member of Technical Staff, Research
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 hire deeply technical staff working in video generation, multimodal, robotics, autonomous vehicles, and adjacent fields. Whether you're building from scratch, scaling training runs, or working on inference, we hire people who can take an idea and make it real.
What you'll do
Push what world models can do past where current diffusion and transformer approaches stop. That might mean new architectures, new training paradigms, or new ways of representing time, dynamics, and interaction.
Take ideas from hypothesis through experiment to working prototype.
Design and run the experiments, distributed training, and inference systems that make breakthroughs possible, and ship the results into models real users touch.
Work shoulder-to-shoulder across research and engineering. Strong work here is recognized by both sides as theirs.
Contribute to the lab's scientific and engineering culture: publishing where it matters, building tools that outlast the project, and engaging with the broader community shaping this field.
Who you are
Deeply technical, with a track record in generative modelling, multimodal learning (visual, audio, text), model-based RL, computer vision, or similar areas. You've either originated work that moved the field.
Comfortable working from first principles. You can define a problem, design experiments to test it, and build the minimal system that proves what's possible.
Energized by ambiguity. You've operated in areas without precedent and built the tools, frameworks, and patterns as you went.
Have a real view on where this field needs to go next, and can defend it. "Bigger model, more compute" is a partial answer.
Thrive in small, focused teams that value autonomy, speed, and tight collaboration over process.
Excited to help define a new category of AI: how AI perceives, learns, and interacts with the world.