Machine Learning Engineer

Forwardrole; Manchester, Cheltenham; Hybrid; GBP 70,000 - 100,000; Full time

Job summary

Forwardrole is seeking specialists in ML and MLOps with machine learning as the core capability, spanning research, prototyping, productionisation and deployment in National Security environments in the UK. Location options include Manchester or Cheltenham with hybrid working and Secure Site requirements.

You'll work with teams that care about the discipline, keep near to research, and drive production-ready ML systems, aiming for reliable deployment and strong engineering practices.

Qualifications

• Mid-level to Senior/Lead ML engineer with core ML capability.
• Active SC clearance minimum, DV/eDV desirable.
• Hybrid working with secure site requirements.

Responsibilities

• Develop ML and MLOps capabilities from research to production deployment.
• Deliver production ML pipelines and monitoring in national security environments.
• Collaborate with Platform and Data Engineers to ensure reliable model performance outside notebooks.
• Work across research and engineering to advance ML systems in production use.

Skills

Python fundamentals

Research mindset

Engineering mindset

Tools

Python

PyTorch

TensorFlow

scikit-learn

AWS

Docker

Linux

CI/CD

Job description

Specialist ML and MLOps teams where machine learning is the core capability, spanning research, prototyping, productionisation and deployment into real National Security environments.National Security

Location: Manchester or Cheltenham
Level: Mid-level through to Senior / Lead
Clearance: Active SC minimum | DV/eDV highly desirable
Working pattern: Hybrid working - Secure Site working required

There are plenty of roles where "AI" is somewhere in the job description.

This isn't really one of those.

I'm working with specialist ML and MLOps teams where machine learning is the core capability, spanning research, prototyping, productionisation and deployment into real National Security environments.

You'll be working with people who genuinely care about the discipline, keep close to the research, experiment with new approaches and still care about getting models into production properly.

What you could be working across

• Python
• PyTorch, TensorFlow or scikit-learn
• LLMs, RAG, agents and evaluation
• ML research and rapid prototyping
• MLOps and production ML pipelines
• Model deployment, monitoring and lifecycle tooling
• AWS, Docker and Linux
• CI/CD and software engineering best practice

The strongest candidates tend to sit somewhere between research and engineering.

You might be taking ideas from papers and applying them to real customer problems, building production ML systems, or working with Platform and Data Engineers to make sure models actually perform reliably outside a notebook.

Why it's worth a look

The teams I'm supporting offer:

• Genuine ML/AI specialism rather than generic consultancy work
• Exposure across research through to production
• Strong technical peers
• Time and encouragement to keep learning
• Real-world impact rather than endless PoCs
• The chance to work across some of the most interesting secure AI problems in the UK

You don't need every framework listed above.

Curiosity, strong Python fundamentals and a genuine interest in how ML systems work in the real world matter more than ticking every box.

Clearance

You'll need active SC as a minimum, with willingness/eligibility to go through higher levels of clearance long-term.