Senior ML Engineer

Department: Technical Capability

Employment Type: Full Time

Location: UK - London

Reporting To: Brian Bassil

Job Title: Senior ML Engineer

Contract Type: Permanent

Location: In terms of location, this role can be based from our Bath, London, Fareham or Bristol offices. We are happy to explore flexible and hybrid working arrangements. Please note that travel to customer sites or to attend meetings will be required.

• Be a UK sole national.
• Have held no other nationality at any time.
• Have continuously resided in the United Kingdom for the past five years.
• Be able to obtain and maintain full UK security clearance in accordance with government vetting standards.
• Provide satisfactory evidence of identity, nationality, and residency as part of the clearance process.

• Private Medical (family coverage)
• Enhanced Pension
• 18 weeks enhanced maternity pay (after a qualifying period of 1 year)
• Family friendly policies
• Committed to an inclusive culture
• Wellbeing Fund - an annual fund for personal hobbies or interests
• 26 Days Annual Leave (plus bank holidays)
• Holiday Trading
• Retail Vouchers
• Professional Subscriptions

• Designing, building, testing, and deploying machine learning systems, applying robust software engineering practices and an in depth understanding of model behaviour, performance, and limitations.
• Selecting and preparing data pipelines for model training and inference. Implement, train, evaluate, and optimise machine learning models, continually improving them through iterative experimentation and additional data.
• Creating scalable and automated ML pipelines, including feature extraction, model training, validation, packaging, deployment, and monitoring.
• Applying standardised engineering and evaluation methods, producing clear technical documentation and communicating design choices, performance outcomes, and limitations.
• Evaluating data integrity and suitability for ML workflows, and advising on transformations, feature representation, and schemas needed for efficient training and inference.
• Applying engineering focused data modelling and system design techniques to create, modify, or maintain ML relevant data structures, feature stores, and associated components. Support alignment of data structures, model interfaces, and infrastructure components to ensure efficient and scalable ML system operation.

• Model Development: Ability to select, train, and tune models (classical ML and deep learning) using frameworks such as PyTorch, TensorFlow, or scikit learn; perform robust validation and error analysis.
• MLOps & Productionisation: Experience containerising and deploying models (e.g., Docker), implementing CI/CD, monitoring, drift detection, and automated retraining on Azure/AWS/GCP as appropriate.
• Software Foundations: Strong engineering skills in Python (typing, testing, packaging); experience with version control (Git) and code review workflows.
• MLOps Engineering: Experience with cloud ML platforms (Azure Machine Learning or AWS/GCP equivalents), CI/CD tooling (GitHub Actions, Azure DevOps), containerisation using Docker, and implementing model monitoring in production environments.
• MLOps Frameworks: Proficiency with tools such as Terraform, MLflow, Airflow, Kubeflow, SageMaker, or Azure ML.

Missing skills? We recognise technology moves quickly and that no one can learn everything. We seek candidates who can adapt and demonstrate the aptitude to learn. With enthusiasm and the right attitude, we can help you discover your potential.

If you are ready to contribute your skills and passion to a dynamic team addressing impactful challenges, we invite you to apply for this exciting opportunity with BMT. Join us in shaping a safer, more efficient, and sustainable future.