VP, Engineering

1 мес. назад

USAC-level

machine learningsoftware engineeringinfrastructuredata platformcomputetooling

Lead the ML platform and infrastructure group, building and scaling engineering across data, evaluation, and compute systems, reporting to CTO.

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.

Own the roadmap and vision for the ML platform across data, evaluation, and compute topics. This consists of software systems, tooling, and infrastructure.
Build and scale the engineering group, across multiple teams and locations
Partner closely with the Research team, Applied ML team, and other technical leaders so platform work stays tied to research velocity
Make the prioritization calls between researchers, leadership and product
Stay close enough to the technical details to drive product vision and get hands on with the code when needed

You'll lead our ML platform and infrastructure group, spanning our data platform, evaluation systems and tooling, and compute. This leader will serve as a trusted partner to the founders and stakeholders across product and technology, and will report directly to our CTO and co-founder.
10+ years of engineering experience with deep expertise in data, evaluation, and compute infrastructure.
You've worked in an ML systems org and know first-hand what slows ML development down.
You’ve led engineering groups of 20 or more across multiple teams and locations
Based in Palo Alto or London, in office 3+ days a week, ideally full time
Energized by working in a fast-paced startup environment and by the company, the mission and platform