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Odyssey

Member of Technical Staff, Infrastructure Engineer

Location
Palo Alto, CA, US
Employment type
Full-time
Level
Staff
Posted
20 August 2026 (about a month ago)

Checked 7 days agoApplications go to the employer, never to RoleSprint

About this role

WHO WE ARE

Odyssey https://odyssey.ml 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.

WHAT WE'RE LOOKING FOR

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.

WHAT YOU’LL DO

- Develop and operate our low-latency model inference platform, ensuring high availability, scalability, and efficient resource utilization for Odyssey’s world models.

- Engineer and scale our core data processing infrastructure (e.g., Flyte, Ray with k8s) to handle petabyte-scale datasets.

- Design, build, and maintain our large-scale, GPU-based training clusters for deep learning, focusing on usability, high throughput and reliability.

- Automate infrastructure provisioning, configuration, monitoring, and alerting using Infrastructure as Code (IaC) principles.

- Drive performance tuning, cost optimization, and reliability improvements across the entire stack.

- Collaborate closely with researchers and product developers to understand their requirements, optimize their workflows, and improve platform usability.

WHO YOU ARE

- Motivated by building for the frontier: you want to shape the compute and infrastructure foundation of a lab redefining how people create and interact with media.

- Strong programming skills (e.g., Python, Go, or similar) and a solid understanding of software engineering best practices.

- Deep, hands-on experience with containerization (e.g., Docker), container orchestration (Kubernetes) and Infrastructure as Code (Terraform).

- Proven experience building and managing large-scale, distributed systems with GPU computational workloads (e.g., compute platforms, data pipelines, or high-availability services).

- Experienced in designing infrastructure for ML workloads where performance, parallelism, and data movement are critical.

- A collaborative mindset and excellent communication skills, with a passion for building developer-friendly platforms.

Our staff is expected to be in office at least three times a week. A lot of our progress comes from working through problems together, and we want you in the room for that.

Locations

  • Palo Alto, CA, US
  • Zurich, CH
  • London, England, GB

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About this listing

Published on Ashby under the board identifier Odysseyml, which is the name the employer’s own job board carries. RoleSprint has not verified the company’s registered or trading name, so it is shown exactly as published rather than tidied up.

RoleSprint is not the employer and not a recruiter. Applications are made on the employer’s own site and never reach us; what RoleSprint does is help you decide whether a role is worth your time and prepare for it if it is.

Published 20 August 2026, last checked 7 days ago. A posting stops being advertised here 90 days after the employer published it, and one the employer takes down is marked closed rather than quietly removed.

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