ML Engineer in City of Westminster

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.

About the Role: We are seeking an experienced Senior ML Engineer to join our team and engage in a diverse range of client projects within the defence, national security, and commercial sectors. At BMT, we are looking to accelerate all of our business through informed and targeted application of ML and LLMs.

As a Senior ML Engineer, you will be responsible for:

• 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.
• Implementing, training, evaluating, and optimising 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.
• Supporting alignment of data structures, model interfaces, and infrastructure components to ensure efficient and scalable ML system operation.

Eligibility:

• 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.

Skills:

• 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), implement 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.

Additional Notes: BMT are passionate about people; we recognise that technology moves quickly and that no one can learn everything, which is why we seek those who can adapt and demonstrate the aptitude to learn. With enthusiasm and the right attitude, we can help you discover your potential. BMT is dedicated to tackling the most crucial engineering challenges of our era, fostering an environment where individuals with exceptional technical expertise provide meaningful, practical solutions. Committed to creating a safer, more efficient, effective, and sustainable future, BMT values diversity, equity, and inclusion, recognising their pivotal role in achieving our business purpose.

Benefits:

• 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