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Lead Machine Learning Engineer

facultyLondonNational Security & Safety
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Experience
Lead
Posted
21 Sept 2026
Status
Open · checked 7d ago

About this role

Lead Machine Learning Engineer at Faculty in London is a senior technical role that suits an experienced machine learning professional looking to lead large-scale AI platforms within national security and AI safety environments. The position involves directing complex artificial intelligence projects, establishing engineering standards, and mentoring team members.

Role Overview

The Lead Machine Learning Engineer oversees the technical direction of complex artificial intelligence and machine learning projects based in London. The professional balances technical trade-offs, guides team priorities, and defends architectural decisions to senior stakeholders while delivering large-scale platforms in high-risk environments.

Key Responsibilities

Design, implement, and maintain reliable and scalable machine learning systems while justifying architectural decisions for production environments.
Drive the development of shared libraries and infrastructure for model deployment, lifecycle management, and continuous integration and continuous deployment pipelines.
Lead model integration with infrastructure by creating application programming interfaces and services for scalable functionality.
Oversee the delivery of multiple complex workstreams and define project problems in high-risk environments.
Ensure reliable model performance by defining testing frameworks and model versioning systems.
Manage and coach multiple individuals, establishing team-wide development goals to improve technical depth and client delivery.
Execute proactive recommendations for adopting new technologies and artificial intelligence frameworks.

Requirements

Expertise in defining technical roadmaps and managing project priorities to deliver high-stakes outcomes.
Mastery of cloud-native ecosystems and orchestration tools such as Kubernetes to automate model lifecycles and CI/CD pipelines.
Proven ability to design large-scale, AI-powered platforms and provide technical justification for architectural decisions.
Expert-level experience in operationalising models within frameworks like TensorFlow or PyTorch.
Experience defining engineering standards and architecture patterns for agentic systems.
Ability to align multi-disciplinary technical teams with business objectives and customer needs.
Eligibility for UK Developed Vetting and willingness to work on site with clients when required.

Skills and Tools

Kubernetes
TensorFlow
PyTorch
CI/CD pipelines
Cloud-native ecosystems

About the Company

Faculty was established in 2014 to build responsible artificial intelligence that transforms customer performance. The company works across government, finance, retail, energy, life sciences, and defence. Its National Security and AI Safety business unit focuses on advancing responsible artificial intelligence deployment to support national security and global stability.

How to Apply

Candidates should apply directly on the official Faculty careers page.

Skills and tech stack

KubernetesTensorFlowPyTorchMachine Learning

Questions candidates ask

What is the location of this job?

The role is located in the United Kingdom, specifically in London.

What clearance or vetting might be required?

Due to the nature of work with government clients, candidates may need to be eligible for UK Developed Vetting and willing to work on-site with clients periodically.

What frameworks and tools are mentioned for operationalising models?

The posting lists TensorFlow, PyTorch, and orchestration tools such as Kubernetes.

What does the interview process involve?

The interview process includes a talent team screen, an introduction to the hiring manager, a pair programming interview, a system design interview, and a commercial and leadership interview.

Does Faculty permit the use of part-time hours?

Yes, Faculty is open to conversations about part-time hours.

Ready to apply?

The application is on the official faculty careers page.

Apply on company site