A leading digital, cyber and AI consultancy supporting UK government and defence customers is looking for multiple Machine Learning Engineers to join its National Security team. These roles offer the opportunity to work on high-impact, real-world AI and ML solutions that directly support national security objectives, using modern cloud-based platforms and production-grade MLOps practices. You’ll work across the full machine learning lifecycle — from rapid experimentation and hypothesis testing through to deploying and supporting robust production systems. Collaborating closely with data scientists, software engineers and senior stakeholders, you’ll help bridge the gap between research and real operational capability in highly regulated environments. What’s on Offer £45,000 – £65,000 salary, depending on experience Hybrid working model London based role Comprehensive benefits package Security clearance bonus Strong career progression pathways Excellent training, upskilling and development opportunities What You Need Hands-on experience developing and deploying machine learning models in Python using frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Experience designing and delivering ML solutions across the full lifecycle, from experimentation to production Strong knowledge of AWS-based ML services (e.g. SageMaker, Lambda, S3) in production environments Experience with experiment design, hypothesis testing, A/B testing and statistical evaluation Proven ability to transition validated models into production-ready systems with appropriate governance Exposure to LLM / Generative AI applications, including prompt engineering and RAG architectures Ability to communicate complex technical concepts clearly to non-technical stakeholders Experience working in cross-functional teams to deliver production solutions Eligibility and willingness to obtain UK Security Clearance Experience with advanced LLM techniques, containerisation, feature stores, vector databases or regulated industries is advantageous but not essential. .