On-Site Defence ML Engineer (SC-Cleared)

Faculty Fellowship; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

Faculty is seeking an on-site/remote-eligible Machine Learning Engineer to design, build, and deploy production-grade ML systems for defence and national security projects. You will own end-to-end ML delivery, collaborating with data scientists and engineers to scale models responsibly.

You will work in a fast-growing team, applying cutting-edge ML practices with a focus on security, ethics, and practical deployment constraints, including on-site work with UK defence clients.

Qualifications

• Experience with the full machine learning lifecycle.
• Deploy trained machine learning models into production environments.
• Experience with common frameworks such as Scikit-learn, TensorFlow or PyTorch.
• Strong Python software engineering practices.
• Cloud architecture, security, deployment, and open-source tools with major cloud providers.
• Experience with containers and orchestration (Docker, Kubernetes).
• Understanding of probability and statistics; familiarity with supervised/unsupervised learning.
• Mentoring junior engineers and cross-functional collaboration.
• Outstanding verbal and written communication.
• Autonomy and ownership in dynamic problem-solving roles.

Responsibilities

• Engineer production-grade software and infrastructure for ML.
• Collaborate with data scientists and engineers to deploy models.
• Develop reusable tools and best practices for ML delivery.
• Support stakeholders to deliver high-impact, scalable ML solutions.

Skills

ML lifecycle

Production deployment

Python

ML frameworks

Cloud architecture

Docker

Kubernetes

Security/compliance

Mentoring

Communication

Tools

Docker

Kubernetes

AWS

GCP

Azure

Scikit-learn

TensorFlow

PyTorch

Job description

Faculty is seeking an on-site/remote-eligible Machine Learning Engineer to design, build, and deploy production-grade ML systems for defence and national security projects. You will own end-to-end ML delivery, collaborating with data scientists and engineers to scale models responsibly.

You will work in a fast-growing team, applying cutting-edge ML practices with a focus on security, ethics, and practical deployment constraints, including on-site work with UK defence clients.