Machine Learning Engineer

The RoleYou'll design, build, deploy and monitor machine learning systems that deliver real value to our customers. You'll work alongside data scientists, data engineers and software engineers, with plenty of opportunity to learn and grow, whether you're early in your career or already have a few years of hands-on experience.What You'll DoDevelop, train and evaluate machine learning models for [e.g. recommendation, forecasting, NLP, computer vision, anomaly detection]Build and maintain production-ready ML pipelines for training, deployment and inferenceTurn data science prototypes into scalable, reliable servicesMonitor model performance in production, detecting drift and retraining as neededWork with data engineers to build and improve feature pipelines and datasetsWrite clean, tested and well-documented Python codeRun experiments, track results and share findings with technical and non-technical stakeholdersContribute to MLOps best practices, including CI/CD, versioning and reproducibilityApply responsible AI principles, including fairness, explainability and UK GDPR complianceWhat We're Looking ForEssential0 to 4 years' experience in machine learning, data science, software engineering or a similar role (graduates and career changers with strong projects are welcome)Strong Python skills and experience with libraries such as scikit-learn, pandas and NumPyHands-on experience with a deep learning framework (PyTorch or TensorFlow)Solid understanding of core ML concepts: supervised and unsupervised learning, model evaluation, feature engineering, overfitting and bias/varianceGood grasp of statistics and maths fundamentalsWorking knowledge of SQL and GitStrong problem-solving skills and the ability to communicate technical ideas clearlyDesirableExperience deploying models via APIs (e.g. FastAPI, Flask) or batch pipelinesFamiliarity with a cloud platform (AWS, Azure or GCP) and ML services such as SageMaker, Vertex AI or Azure MLExposure to MLOps tools such as MLflow, Kubeflow, Airflow or Weights & BiasesExperience with Docker, Kubernetes or CI/CD pipelinesExperience with LLMs, NLP, or generative AI (e.g. Hugging Face, LangChain, RAG)Degree or Master's in Computer Science, Maths, Statistics, Engineering or a related field, or equivalent practical experience