---
title: 'Member of Technical Staff, ML Performance at Odyssey'
canonical: 'https://feeny.ai/job/member-of-technical-staff-ml-performance-odyssey-palo-alto-th4pzfq427tq'
type: 'job'
last_seen: '2026-10-15'
---

# Member of Technical Staff, ML Performance at Odyssey

- **Company:** Odyssey
- **Location:** Palo Alto, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-03-11
- **Last confirmed live:** 2026-10-15
- **Apply:** https://jobs.ashbyhq.com/odysseyml/28c99a01-1e1a-498c-adca-f2271656e824/application

**Skills:** Inference Optimization, Machine Learning, PyTorch, TensorFlow, JAX, Triton, NVIDIA GPU, Distributed Training

> Optimize machine learning models and inference infrastructure for large-scale deployment, focusing on speed, reliability, and scalability. The role involves designing distributed training strategies, partnering with research teams, and developing tools to identify performance bottlenecks using cutting-edge GPU techn...

## 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

We're seeking those who are obsessed with gaining every last drop of performance from complex systems. We're building inference infrastructure to scale to hundreds of thousands of users within a year, while also working with massive, ever-growing datasets and models in training. Your focus will be ensuring our models deliver exceptional speed, reliability, and scalability in both the training and inference phases, optimizing efficiency to minimize TFLOPS per user and training compute cost.

## What you'll do

- Optimize models that will be used in real-time by hundreds of thousands of users.
- Design and implement distributed training strategies to reduce training time and resource consumption on large GPU clusters.
- Partner with our elite team of ML researchers and engineers to ensure model architectures are highly performant from conception.
- Develop sophisticated tools to identify performance bottlenecks and stability issues in both training and serving environments.
- Pioneer innovative approaches, frameworks, and system designs that enhance performance metrics across our model development and inference infrastructure.
- Have significant autonomy in technical decisions.
- Use the latest-generation GPUs.

## Who you are

- 8+ years of software engineering experience, with significant work in ML performance.
- Deep insight into modern machine learning architectures with a natural instinct for performance optimization, particularly distributed training and inference.
- Track record of owning projects end to end.
- Problem-solving mindset with the ability to acquire new skills as needed.
- Proficiency with PyTorch (or TF/JAX) and Triton as well as NVIDIA GPU ecosystems and optimization stacks.
- Highly metric-based.

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.

## 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.

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