---
title: 'Member of Technical Staff, Foundation Models at Odyssey'
canonical: 'https://feeny.ai/job/member-of-technical-staff-foundation-models-odyssey-palo-alto-0h5g5ayn20dg'
type: 'job'
last_seen: '2026-09-17'
---

# Member of Technical Staff, Foundation Models at Odyssey

- **Company:** Odyssey
- **Location:** Palo Alto, CA
- **Employment:** full-time
- **Posted:** 2026-07-24
- **Last confirmed live:** 2026-09-17
- **Apply:** https://jobs.ashbyhq.com/odysseyml/1a1a2cc0-8a1a-4cbb-8ffa-879161b06e14

## Job description

## 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

The right person will have a deep interest in building large foundation world models, and in the scaling laws that tell you which ones are worth building. You will want to train them from scratch, at the scale that takes: runs across thousands of GPUs, data mixtures measured in years of video, and an interactive model at the end that has to hold up frame by frame under a human's hands. You will treat that as one system, data, architecture, training, inference, evaluation, rather than as six specialties, and go wherever the bottleneck is. This is a cutting edge research area that is not yet mature, so you will be working at the cusp of what’s possible. Most new experiments in this area will fail, your focus will be on maximally learning from failed experiments to increase the chances of eventual success.

## What you’ll do

- Learn what makes large real-time world models tick. Understand how data, architecture, scale, and diffusion algorithms interact.
- Run scaling studies and use them: fit scaling laws over model size, data, and compute, and let them pick the next large run rather than intuition alone.
- Own world model training at scale, large distributed runs across thousands of GPUs, the data mixtures that feed them, and the loss and stability work that keeps them alive for weeks.
- Implement state of the art ML algorithms, define metrics, and relentlessly iterate on leaderboards.
- Work end to end across the stack, from data pipelines and tokenizers through training to real-time inference and evaluation.
- Be part of a team that is defining and leading the world model space.
- Exploit the latest features on modern GPUs to increase training and inference efficiency.
- Take ownership of the full ML stack, including the core frameworks that Odyssey researchers and product engineers alike rely on.

## Who you are

- 2+ years of software engineering experience, with significant work in ML performance.
- 4+ years of ML engineering experience, or a PhD in a related field.
- Hands-on experience training large models, pretraining at multi-node scale, and the debugging that comes with it.
- Comfortable reasoning about scale: scaling laws, compute and data budgets, and what a small-scale ablation does and does not predict.
- A holistic ML engineer — happy to move between data, model, systems, and evaluation, and to own the whole path from an idea to a shipped model.
- Track record of owning projects end to end.
- Not shy to touch any stage of an ML pipeline.
- Proficiency with PyTorch (or TF/JAX).
- Highly experiment driven.

## About Odyssey

## Company Overview
- **One-liner**: Odyssey is an AI lab pioneering general-purpose world models—causal, interactive, real-time simulations that learn from video and multimodal data to enable new forms of intelligence.
- **Entity Type**: Private (Series B, raised $310M)
- **Headquarters**: Palo Alto, California, United States (also offices in London, England and Zurich, Switzerland) [builtin.com](https://builtin.com/company/odyssey-odysseyml)
- **Founded**: 2023 [builtin.com](https://builtin.com/company/odyssey-odysseyml)
- **Founders**: Oliver Cameron (Co-Founder & CEO), Jeff Hawke (Co-Founder & CTO) [odyssey.ml/careers](https://odyssey.ml/careers)

## Core Business
- **Primary industry/industries**: Artificial intelligence, machine learning, world modeling, robotics, simulation.
- **Target customers**: B2B (developers, enterprises in robotics, gaming, healthcare, advertising, retail, defense) and B2C (future consumer applications like interactive entertainment, personal assistants, immersive fitness).
- **Mission or purpose statement**: "We learn the world to make it better." [odyssey.ml/about](https://odyssey.ml/about)

## Products & Services
- **[Odyssey-2](https://odyssey.ml/)**: A general-purpose world model that generates minutes-long, interactive, real-time simulations from text or image prompts. It streams frame-by-frame and can be interacted with by multiple participants (human or AI). Designed for applications in robotics rehearsal, gaming, interactive advertising, virtual try-ons, and more.
- **[Agora-1](https://odyssey.ml/about)**: A multi-agent world model enabling multiple participants—human or AI—to share and interact within the same world simulation in real-time. Built on a novel RL-driven adversarial framework to improve world model performance.
- **[Starchild-1](https://odyssey.ml/about)**: The first real-time multimodal world model, going beyond visual observation to learn from richer multimodal interaction with the world.

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: $310M Series B funding (latest round) [odyssey.ml/about](https://odyssey.ml/about)
- **Notable Investors/Partners**: Backed by Jeff Dean (Chief Scientist, DeepMind), Soumith Chintala (CTO, Thinking Machines), Max Jaderberg (President, Isomorphic Labs) [odyssey.ml/careers](https://odyssey.ml/careers); also advised/invested by Tim Rocktäschel (Co-Founder, Recursive) [odyssey.ml/careers](https://odyssey.ml/careers)
- **Growth Signals**: Rapid hiring (16+ open roles across research, engineering, product, policy, HR, and operations) [linkedin.com](https://www.linkedin.com/company/odysseyml); launched breakthrough world models (Odyssey-2, Agora-1, Starchild-1); offices in 3 global tech hubs; employee headcount growing ~33% year-over-year (approx. 37–46 employees) [linkedin.com](https://www.linkedin.com/company/odysseyml) [builtin.com](https://builtin.com/company/odyssey-odysseyml)

## Competitive Advantages
- **Pioneering approach**: Odyssey is one of the first labs to focus exclusively on general-purpose world models, shifting beyond language models to simulate physics, causality, and intelligence.
- **Top-tier talent**: Team recruited from leading AI labs (DeepMind, Meta, Waymo, Cruise, Wayve) and companies like Apple and Roblox [linkedin.com](https://www.linkedin.com/company/odysseyml).
- **Compute & infrastructure**: Building inference infrastructure capable of scaling to hundreds of thousands of users within a year while minimizing TFLOPS per user [odyssey.ml/careers](https://odyssey.ml/careers).
- **Research output**: Publicly released state-of-the-art models (Odyssey-2, Agora-1, Starchild-1) that materially advance physical accuracy and interactivity in world models [odyssey.ml](https://odyssey.ml/).

## Strategic Focus
- **Current priorities**: Scaling world model inference for real-time, interactive consumer and enterprise products; pushing research boundaries in multimodal learning, reinforcement learning, and multi-agent simulation; building the "financial engine" for a compute-intensive AI business (capital allocation, unit economics) [odyssey.ml/careers](https://odyssey.ml/careers).
- **Direction for growth**: Applying world models to robotics (sim-to-real rehearsal), gaming, healthcare, advertising, retail, defense, education, and personal assistant systems. Aiming to "proliferate interactive intelligence into the world" [odyssey.ml](https://odyssey.ml/).

## Why Work Here
- **Culture and autonomy**: Odyssey prizes "autonomy and ownership" – deep work with accountability, and the freedom to tackle meaningful, open-ended scientific problems [odyssey.ml/careers](https://odyssey.ml/careers).
- **Team**: Collaborate with researchers and engineers from leading labs who have driven major AI advancements. Strong peer group focused on original science [odyssey.ml/careers](https://odyssey.ml/careers).
- **Work policy**: Hybrid model – employees work from physical offices in Palo Alto, London, or Zurich. No remote-only option; typical time on-site not specified [builtin.com](https://builtin.com/company/odyssey-odysseyml).
- **Compensation & benefits**: Competitive salary and equity grants reflecting the demands of breakthrough AI research. Benefits include healthcare, disability insurance, 401(k), generous parental leave, PTO, company socials, and wellness initiatives [builtin.com](https://builtin.com/company/odyssey-odysseyml).
- **Notable for job seekers**: Rapidly scaling (raised $310M, hiring across research, engineering, product, and operations). Opportunity to shape a nascent category (world models) from the ground up.

## Sources
1. [odyssey.ml/careers](https://odyssey.ml/careers) – Careers page with team, culture, and benefits details.
2. [odyssey.ml/about](https://odyssey.ml/about) – About page with mission, funding, and model announcements.
3. [odyssey.ml](https://odyssey.ml/) – Homepage with product descriptions and applications.
4. [builtin.com](https://builtin.com/company/odyssey-odysseyml) – Built In company profile with employee count, perks, and office locations.
5. [linkedin.com](https://www.linkedin.com/company/odysseyml) – LinkedIn company page with headcount, growth, and talent sources.

## Other roles at Odyssey

- [Strategic Partnerships, Foundation Models](https://feeny.ai/job/strategic-partnerships-foundation-models-odyssey-palo-alto-8ad077mx6nt9) — Palo Alto, CA
- [Controller](https://feeny.ai/job/controller-odyssey-palo-alto-1anypxk5yk02) — Palo Alto, CA
- [Member of Technical Staff, Infrastructure Engineer](https://feeny.ai/job/member-of-technical-staff-infrastructure-engineer-odyssey-palo-alto-78e1qwcgzrya) — Palo Alto, CA
- [Research Internship](https://feeny.ai/job/research-internship-odyssey-palo-alto-v0rv7s8cfzfd) — Palo Alto, CA
- [Executive Business Partner](https://feeny.ai/job/executive-business-partner-odyssey-london-dgfbmxp8z5zn) — London, United Kingdom
- [Member of Technical Staff, Data Engineering](https://feeny.ai/job/member-of-technical-staff-data-engineering-odyssey-palo-alto-n16zsqmcv70j) — Palo Alto, CA
- [Member of Technical Staff, Applied Research](https://feeny.ai/job/member-of-technical-staff-applied-research-odyssey-palo-alto-k90agz5z47tm) — Palo Alto, CA
- [VP, Engineering](https://feeny.ai/job/vp-engineering-odyssey-palo-alto-tka73j1qbv60) — Palo Alto, CA
- [Member of Technical Staff, TLM: Research Scientist](https://feeny.ai/job/member-of-technical-staff-tlm-research-scientist-odyssey-palo-alto-8d6e4yxm6gc9) — Palo Alto, CA
- [AI Resident](https://feeny.ai/job/ai-resident-odyssey-palo-alto-rkf461yxgdzs) — Palo Alto, CA