Machine Learning Engineer - Hybrid

Senior Machine Learning Engineer x2 days a week on UK client site, optional London HQ visits

Were partnering with a specialist AI and data consultancy that designs and deploys bespoke machine learning systems across sectors such as national security, defence, critical infrastructure, and digital public services. Their focus is on delivering safe, production-grade AI solutions that drive real-world outcomes for complex, high-stakes environments.

This is a fast-paced, technically elite environment, ideal for someone who thrives on solving operational challenges, building robust MLOps infrastructure, and leading the delivery of AI systems at scale.

As a Senior Machine Learning Engineer, youll be part of cross-functional delivery teams working on technically complex, high-impact AI projects. Youll play a central role in designing and building the ML architecture (from infrastructure and deployment to tooling and automation) to ensure that solutions are not only technically sound, but also scalable, maintainable, and secure.

Youll work alongside data scientists, engineers, designers, and product stakeholders often embedded within mission-critical delivery environments.

Lead the design and build of production-ready machine learning pipelines and systems
Develop infrastructure and tooling to enable deployment, monitoring, and retraining of ML models
Work across the full AI delivery lifecycle, from architecture and integration to performance optimisation
Mentor junior engineers and shape internal technical standards for software quality, reliability, and reproducibility
Strong software engineering skills, especially in Python.
Experience building robust systems for ML applications
Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch)
AWS, Azure, GCP) and a good understanding of architecture, security, and scaling
Solid grasp of ML fundamentals: supervised/unsupervised learning, statistical modelling, evaluation
A pragmatic approach to engineering capable of balancing speed, risk, and delivery in complex environments