Machine Learning Engineer

Faculty

UK - London💼 Full-time🗓 2026-02-23 → 2026-09-26

Core

Build and deploy production-grade machine learning systems and scalable infrastructure for financial services clients.

Role type

Senior Machine Learning Engineer (Production & Infrastructure)

Builds

Production-grade ML software, tools, and infrastructure for financial institutions

Domain

Financial Services / Applied AI

Deliverable

production ML models

Required skills

Machine learning lifecycle, Python, software engineering best practices, cloud platforms (AWS/Azure/GCP), container orchestration (Docker/Kubernetes), probability and statistics

Preferred skills

Technical advisory, cross-functional collaboration, architectural decision-making

Technologies

Scikit-learn, TensorFlow, PyTorch, AWS, Azure, GCP, Docker, Kubernetes

Responsibilities

Build and deploy production-grade ML software and infrastructure; Create reusable, scalable solutions; Collaborate with engineers and commercial leads; Lead technical scoping and architectural decisions; Define standards for deploying ML at scale; Act as a technical advisor to customers

Seniority

Senior, hands-on IC

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About Faculty

Faculty is one of the world's leading applied AI companies, helping many of the organisations that shape our world to adopt AI successfully and safely. We play an important role in the emerging AI safety ecosystem. We already have many of the key Frontier Labs as clients, including Open AI and Anthropic, for whom we provide third-party red teaming, technical testing and other AI safety services. And we work with the UK government and other international governments on AI safety, including helping set up the AI Security Institute and delivering technical work which catalysed the first global AI