Odyssey builds, secures and integrates capabilities and technologies to meet tomorrow’s mission requirements. We enhance operational readiness through comprehensive program support. Backed by a16z, General Catalyst and GV.
About the role
Build and run data pipelines for large-scale multimodal datasets, from raw video, robotics, and audio through to curated, enriched training data. Pull useful signals out of raw data: detecting speakers, isolating background audio, tracking points and features in video, and other signals that affect what the models learn.
What they're looking for
- You're good at figuring things out. Give you an ambiguous, poorly-defined data problem and you'll work out what actually matters, then go build it. This is the trait we care about most
- You like the data work itself. Digging through messy multimodal data to find signal is the interesting part for you, not a means to an end
- You can switch between platform and infrastructure work and research-facing feature work, and you see how the two feed each other
- You've worked with real video and/or audio data and know what it takes to process it at scale
- You're comfortable working alongside researchers, translating what they need into concrete data work
- Roughly 1 to 5 years of relevant experience. We're open on seniority and hire for the person, not the title
More about this role
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.
Data is fast becoming one of the biggest bottlenecks in building world models. Our models are only as good as the data behind them, and getting that data right is one of the hardest and most important problems we have. We're looking for a data engineer who wants to be the person figuring it...
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