2 of 2 XGBoost Jobs in the City of London

recommendation systems, optimisation, or marketing analytics. Deep understanding of ML fundamentals across the full lifecycle. Hands‐on experience with ML frameworks (scikit‐learn, XGBoost, PyTorch, TensorFlow, LightGBM). Strong exposure to LLMs, prompt engineering, RAG, and evaluation frameworks. Familiarity with MLOps tooling: CI/CD, experiment tracking, model registries, monitoring ...

many of the following areas. Expectations scale by level. Hands-on experience building ML models in Python using libraries such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Experience deploying ML workloads on AWS, including services such as SageMaker, Lambda, and S3. Understanding of experiment design, evaluation techniques, and statistical reasoning. ...