Machine Learning Engineer
Anson Mccade ·
Job Description Machine Learning Engineer£65,000 GBPOnsite WORKINGLocation: Central London, Greater London - United Kingdom Type: PermanentAn opportunity is available for an experienced Senior Machine Learning Engineer to design, build and operationalise advanced machine learning solutions that directly support UK national security objectives.
This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation and hypothesis testing through to secure, production-grade deployment, using a modern AWS-based MLOps and LLMOps platform.
The RoleThe successful candidate will balance rapid experimentation with production readiness, prototyping and validating machine learning and generative AI approaches while ensuring successful models integrate seamlessly into live operational systems.
This is a high-impact role at a pivotal point in the adoption of AI, machine learning and large language models across critical national systems, offering the chance to deliver real-world outcomes at scale. Key Responsibilities Designing, developing and optimising machine learning models across traditional ML use cases (forecasting, classification, anomaly detection) and GenAI / LLM solutionsLeading experimentation cycles, including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standardsTransitioning validated experiments into production-ready ML services, collaborating closely with engineering teams on deployment and monitoringBuilding scalable ML pipelines using AWS services and modern experiment tracking frameworksDeveloping and integrating LLM-powered capabilities for evaluation, tracing and production monitoringImplementing robust experiment tracking, model versioning and reproducibility, ensuring full auditabilityDesigning feature engineering strategies and contributing to feature store developmentMonitoring live models, analysing performance and driving continuous improvementApplying responsible AI principles, including explainability, robustness and fairnessCommunicating experimental results and production outcomes to stakeholders, highlighting operational and strategic valueMentoring junior engineers and promoting best practices across the teamAbout the CandidateThe ideal candidate will bring strong hands-on experience in machine learning engineering, with the ability to translate experimental success into reliable, scalable systems.
Essential experience includes: Commercial experience developing and deploying machine learning models in PythonProficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlowStrong experience delivering ML solutions using AWS services (e.g.
SageMaker, Lambda, S3)Expertise in experiment design, including hypothesis formulation, A/B testing and statistical evaluationProven experience moving models from experimentation into production with appropriate governance and quality controlsHands-on experience with MLOps tooling such as MLflow, Weights & Biases or Data Version ControlPractical experience building LLM / GenAI applications, including prompt engineering and retrieval-augmented generation (RAG)Familiarity with LLMOps frameworks such as LangChain, LangSmith or LangGraphUnderstanding of model validation, evaluation techniques and production monitoringExperience working in cross-functional teams from problem definition through to deliveryStrong communication skills, with the ability to explain complex concepts to non-technical audiencesSound judgement in applying AI appropriately and recognising when non-AI approaches are more suitableDesirable Experience Advanced LLM techniques, including agents, tool use and agentic workflowsExperience with vector databases (e.g.
Pinecone, Weaviate, pgvector)Feature store technologies such as Feast or AWS Feature StoreContainerisation and orchestration using Docker, Kubernetes or ECSInfrastructure as Code using Terraform or CloudFormationLarge-scale data processing frameworks such as Spark or DaskKnowledge of data governance, compliance and regulated environmentsExperience delivering solutions within highly regulated industries such as government, finance or healthcareSecurity ClearanceThis role requires UK Security Clearance.
Applicants must already hold clearance or be eligible and willing to undergo the vetting process. Reference: AMC/RHU/MLE#ryhu