Odyssey is pioneering AI video you can both watch and interact with in real-time.
Odyssey was founded in late 2023 by Oliver Cameron (Cruise, Voyage) and Jeff Hawke (Wayve, Oxford AI PhD), two veterans of self-driving cars and AI. They’ve since recruited a world-class team of AI researchers from Waymo, Tesla, Meta, Cruise, Wayve, and Microsoft.
Odyssey has raised significant venture capital from GV, EQT Ventures, Air Street Capital, DCVC, Elad Gil, Garry Tan, Soleio, Jeff Dean, Kyle Vogt, Qasar Younis, Guillermo Rauch, Soumith Chintala, and researchers from OpenAI, DeepMind, Meta, and Midjourney. Ed Catmull, the founder of Pixar, serves on Odyssey’s board.

WHAT WE’RE LOOKING FOR

We’re seeking a data engineer to own our ML/data platform. This role has different titles at many companies, and will be a mixture of infrastructure, tooling, and data pipelines that enable our researchers to efficiently work with multimodal data (images, video, 3D, and more), conduct experiments, and seamlessly move models to production. You’ll have significant autonomy in technical decisions and the opportunity to grow into a technical leadership role as we scale.

THE REQUIRED SKILLS & EXPERIENCE

• 5+ years of software engineering experience, with significant work in data platforms.
• Strong Python development and system design expertise.
• Deep experience with data pipeline development and ETL processes.
• Production Kubernetes experience and container orchestration expertise.
• Hands-on experience with data-oriented ML infrastructure tools (experiment tracking, feature stores, model registries).
• Proficiency with cloud platforms (AWS/GCP/Azure).
• Experience with data versioning and experiment tracking systems.
• Understanding of ML workflows and researcher needs.

• Design and implement our Kubernetes-based ML data platform from the ground up.
• Build scalable data pipelines that support both research experimentation and production deployment.
• Create systems for dataset versioning, experiment tracking, and model lifecycle management.
• Develop tools and interfaces that make it easy for researchers to find, enrich, and version multimodal data.
• Establish best practices for reproducibility and production readiness.
• Collaborate closely with ML researchers to understand and optimize their workflows.