Member of Technical Staff, Research

Who we are Odyssey is an AI lab pioneering general-purpose world models: causal, multimodal systems that learn to predict and interact with the world over long horizons, while generating real-time, interactive simulations from any starting point. This foundational technology promises to revolutionize robotics, science, healthcare, education, gaming, defense, and beyond. What we're looking for We’re looking for a deeply technical and creative researcher who thrives on invention. You’re motivated by the unknown, energized by turning abstract ideas into concrete systems, and comfortable bridging the gap between research and product. You’re excited by the chance to pioneer general-purpose world models capable of real-time generation, understanding, and interactivity. What you'll do Pursue original research into the foundations of world models: representation, temporal coherence, causality, control, and long-horizon imagination. Formulate and own an independent research agenda: identifying unsolved questions, designing hypotheses, and developing algorithms that could redefine what these models can do. Explore new architectures, learning objectives, and training paradigms that move beyond today’s diffusion and transformer approaches. Develop conceptual frameworks and experimental systems that deepen our understanding of how models perceive and respond to user intent and real-world dynamics. Collaborate closely with our engineering and infrastructure teams to turn foundational insights into prototypes that demonstrate new capabilities, not just incremental improvements. Contribute to the scientific culture of the lab: publishing, mentoring, and engaging with the broader research community to shape the field of general-purpose world models. Who you are A researcher with deep expertise in machine learning and a track record of original contributions to generative modeling, video synthesis, multimodal learning, or related areas. Experienced in conducting long-horizon, exploratory research that produces conceptual and algorithmic breakthroughs beyond scaling improvements alone. Comfortable working from first principles: defining new problems, designing experiments to test them, and building minimal systems to prove what’s possible. Motivated by understanding as much as by performance: you care about how and why models work, not only that they do. Thrives in a small, focused lab environment that values autonomy, deep thinking, and tight research collaboration. Passionate about establishing the scientific underpinnings of a new medium—helping define how AI perceives, learns, and interacts through pixels over the next decade.