Senior Machine Learning Engineer

In the office ~x2/3 days a week in London

About the Company

We’re working with a specialist AI consultancy that delivers tailored machine learning systems for organisations operating in high-complexity domains. Their clients span industries such as finance, defence, legal services, government, and energy. The core focus is on building safe, production-ready AI that performs in demanding real-world settings.

This is a fast-paced and technically rigorous environment, ideal for someone who enjoys solving practical challenges, contributing to engineering excellence, and building reliable infrastructure around machine learning systems.

What You’ll Be Doing

• Design, build, and maintain machine learning pipelines that are robust, scalable, and suitable for production environments




• Develop internal tooling and infrastructure to support model deployment, monitoring, and retraining workflows




• Contribute across the AI delivery lifecycle, including system architecture, integration planning, and performance tuning




• Work closely with clients and cross-functional teams to ensure technical solutions meet real-world constraints and expectations




• Help define engineering standards, mentor more junior developers, and support internal capability building




• Collaborate on improving internal processes and best practices for MLOps and AI platform delivery

What They’re Looking For

• Strong programming skills in Python with experience building backend systems




• Background in developing infrastructure to support machine learning projects




• Practical experience deploying models using frameworks such as PyTorch, TensorFlow, or scikit-learn




• Familiarity with tools like Docker and Kubernetes for containerised deployments




• Experience working with cloud platforms such as AWS, Azure, or GCP, including an understanding of cost, scaling, and security trade-offs




• Good understanding of machine learning fundamentals, including evaluation metrics and modelling best practices




• Clear communication skills and the ability to collaborate effectively with both technical and non-technical teams




• Bonus: experience in fast-moving or delivery-focused environments where pragmatism and flexibility are key

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