We're looking for engineers who love the craft of building: people who write elegant, scalable machine learning code, care about performance, and deeply understand the research to shape it. You move fluidly between modeling and systems, are are unafraid to tackle ambiguous technical challenges, and take pride in building the infrastructure and tools that make breakthroughs possible

We are looking for an engineer who thrives on building the engines that make groundbreaking research and products possible. You think in systems, love performance, and get energy from turning theoretical bottlenecks into beautifully efficient reality. You're excited to design and support infrastructure not just for scale, but for speed, creativity, and discovery. You want to build the compute substrate that lets Odyssey's world models imagine, act, and interact in real time

We're seeking those who are obsessed with gaining every last drop of performance from complex systems. We're building inference infrastructure to scale to hundreds of thousands of users within a year, while also working with massive, ever-growing datasets and models in training. Your focus will be ensuring our models deliver exceptional speed, reliability, and scalability in both the training and inference phases, optimizing efficiency to minimize TFLOPS per user and training compute cost

We need a deeply experienced Data Platform Lead to take full ownership of our data practice. This is a crucial technical leadership position focused on architecture, strategy, and getting things done. You should be an expert with serious, hands-on data engineering chops, capable of defining the long-term architectural vision while still diving into the code. Success in this role requires a complete understanding of the data lifecycle: from partnering with Operations to source data, designing robust data recipes and ensuring the resulting data assets are optimized for our world models