Founding Machine Learning Infrastructure Engineer

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Build the infrastructure to serve personal AI models privately and at scale.

We're building the first truly private, personal AI – one that learns your skills, judgment, and preferences without big tech ever seeing your data.

Our core ML systems challenge: how do we serve the world’s best personal model, at low cost and high speed, with bulletproof privacy?

What you'll do

• Build the infrastructure that lets us create & deploy thousands and eventually millions of personalized finetuned models for our customers

• Monitor & optimize in-the-wild model serving performance to hit low latency & cost

• Interface with the TEE-based privacy stack that lets us guarantee user data & models can only be seen & used by the user—not even us—and integrate the privacy architecture with the finetuning & inference code

You have

A deep understanding of the machine learning stack. You can dive into the details of how transformers work & performance optimization techniques for them. You have a mental model of GPUs sufficient to reason about performance from first principles. You can drill down from ML code to metal.

Ability to execute quickly. We ship fast and fail fast so we can win faster. The challenge of human relevance in a post-AGI world isn’t going to solve itself.

A missionary mentality. We’re a mission-driven company, looking for mission-first people. If you’re passionate about ensuring AI works for people (and not the other way around), you’ve come to the right place.

Ready to roll up your sleeves. We're an early stage startup, so we’re looking for someone who can wear many hats.

Experience you may have

• Work at a fast-paced AI startup, or top AI lab.

Experience deploying ML systems at scale. You might have worked with frameworks like vLLM, S-LoRA, Punica, or LoRAX.

Experience with privacy-first infrastructure. You’re familiar with confidential computing & ability to reason about both technical and real-world confidentiality and security. You may have worked with secure enclaves, TEEs, code measurement & remote attestation, Nvidia Confidential Computing, Intel TDX or AMD SEV-SNP, or related confidential computing technologies.

We encourage speculative applications; we expect many strong candidates will have different experience or unconventional backgrounds.

What we offer

• Generous compensation. We’re competitive with the top UK startups, because we believe the best talent deserves it.

• Meaningful equity. We’re a seed stage startup with massive growth potential. You’ll be getting in early.

World-class expertise. We’re based in a top AI research hub in London, and are backed by AI experts like Juniper Ventures, Seldon Lab, and angels at Anthropic and Apollo Research. You’ll have access to some of the best AI expertise in the world.

Massive impact. Our mission is to keep people in the economy well after AGI. If you want to live in a world that’s still run by humans for humans, come help us make it happen.

About Workshop Labs

We’re building the AI economy for humans. While everyone else tries to automate the world top-down, we believe in augmenting people bottom-up.

Our vision is for everyone to have a personal AI aligned to their goals and values, helping them stay durably relevant in a post-AGI economy. As a public benefit corporation, we have a fiduciary duty to ensure that as AI becomes more powerful, humans become more empowered, not disempowered or replaced.

We’re an early stage startup, backed by legendary investors like Brad Burnham and Matt McIlwain, visionary product leaders like Jake Knapp and John Zeratsky, philosopher-builders like Brendan McCord, and top AI safety funds like Juniper Ventures. Our investors were early at Anthropic, Palantir, Slack, Prime Intellect, DuckDuckGo, and Goodfire. Our advisors have held senior roles at Anthropic, Google DeepMind, and UK AISI.

Our co-founders have previously done ML research that was used to evaluate OpenAI models pre-deployment, lead product verticals at the world’s premier education-about-AI company, won political campaigns, and studied at Oxford & Cambridge.

Their essay series on AI’s economic impacts and the technology we’ll need to keep humans relevant, The Intelligence Curse, has been covered in TIME, The New York Times, and AI 2027.