Senior Machine Learning Engineer
You will work with Python, PyTorch, TensorFlow, scikit-learn, Docker, Kubernetes, and AWS/Azure/GCP. This role is at an AI consultancy that delivers production-ready machine learning systems for clients in complex domains like finance and defence.
Free Tailor for ATS: 10/10 runs left
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
If this role interests you and you would like to find out more (or find out about other roles), please apply here or contact us via niall.wharton@Xcede.com (feel free to include a CV for review).