Lead ML Engineer: Architect & Scale AI Solutions

Women in Data®; United Kingdom; On-site; GBP 90,000 - 130,000; Full time

Job summary

Faculty is seeking a Lead Machine Learning Engineer to steer the technical direction and delivery of complex AI and software projects. You will act as a technical expert across solution architecture to client deployments, ensuring reliable and scalable systems.

This role combines deep technical execution with strong leadership, driving innovation, mentoring teams, and building reusable frameworks that accelerate client delivery across multiple engagements.

Qualifications

• Proficient Python and production-grade software engineering.
• Experience with at least one compiled language (Go/Java/Rust/TypeScript).
• Expert in at least one major cloud provider (Azure/GCP/AWS).
• Hands-on with containerisation and orchestration (Docker, Kubernetes).
• Able to mentor engineers and lead teams to deliver complex AI/software projects.

Responsibilities

• Set technical direction for ML and software projects, balancing trade-offs.
• Architect and maintain scalable ML/software systems and justify architectural choices.
• Define project roadmaps and oversee multi-workstream delivery in high-risk environments.
• Develop reusable resources and guide engineers in contributing to them.
• Lead hiring, select talent, and mentor team members to grow capabilities.
• Adopt new technologies and optimize ways of working to stay ahead.

Skills

Python

Compiled language

Cloud platforms

Docker

Kubernetes

Leadership

Communication

Tools

Docker

Kubernetes

Job description

Faculty is seeking a Lead Machine Learning Engineer to steer the technical direction and delivery of complex AI and software projects. You will act as a technical expert across solution architecture to client deployments, ensuring reliable and scalable systems.

This role combines deep technical execution with strong leadership, driving innovation, mentoring teams, and building reusable frameworks that accelerate client delivery across multiple engagements.