Senior MLops (Full Stack) Engineer | London | Foundation Models
What you’ll do
Build and maintain APIs (FastAPI or similar) to serve ML models
Design and manage robust ML infrastructure using Kubernetes, Docker, and Terraform
Deploy machine learning models into production and optimize them for performance
Collaborate with ML teams to streamline training, deployment, and monitoring
Build internal tools and dashboards (e.g., in React or Vue) for analytics and observability
Own CI/CD pipelines and drive infrastructure automationWhat you’ll bring
5+ years’ experience in backend or infrastructure-focused engineering roles
Strong Python and API development skills (FastAPI, Flask, etc.)
Proven experience with model deployment, containerization, and orchestration (K8s, Docker)
Infrastructure-as-code experience (Terraform, Helm, etc.)
Familiarity with cloud platforms like AWS, GCP, or Azure
Bonus: Frontend experience (React, Vue.js) for building internal tools
Why Join Us?
🌍 Tackle the biggest challenge in AI – Be part of the mission to bend the curve on compute costs, energy waste, and emissions in the LLM arms race. Our optimiser is redefining how the world trains and serves large models.
🧠 Work on the frontier – You’ll engineer the infrastructure behind cutting-edge AI systems — pushing the boundaries of speed, efficiency, and scale with a team that lives at the intersection of ML, systems, and optimisation research.
🚀 High-impact, high-autonomy – We’re a lean, expert-led team where your work ships fast, matters deeply, and scales globally. Expect ownership, speed, and the freedom to build without bureaucratic drag.
💥 Foundation model as infra – Our optimiser is itself a foundation model. You’ll help serve, adapt, and scale it in the wild — an opportunity few engineers will ever get.
💸 Equity that means something – You’re not late to the party. Join at a time when your equity still reflects the upside you help create.u
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