6 of 6 Remote/Hybrid XGBoost Jobs in London

Machine Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version ...

commercial experience in machine learning or data science Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoost Exposure to AWS services (e.g. S3, Lambda, SageMaker) Understanding of core ML concepts: model evaluation, validation, and experimentation Familiarity with MLOps or experiment tracking tools (e.g. ...

knowledge of Spark, SQL or other data-oriented programming language and are proficient with standard data wrangling and modelling libraries (e.g. Pandas, Sklearn, Keras, XGBoost, LightGBM) You're collaborative and pragmatic with great communication skills You're collaborative and pragmatic with great communication skills What ...

SQL. Confident working with large, complex, or messy datasets. Experience applying machine learning techniques such as gradient-boosted models, with exposure to tools like XGBoost or CatBoost. Ability to form structured analytical approaches, make sensible assumptions, and communicate your reasoning clearly. Comfortable mentoring others and contributing to a cooperative team ...

Machine Learning Strong Understanding of what it actually takes to run ML Systems in Production Hands-On Experience with Deep Learning Frameworks (TensorFlow, PyTorch, XGBoost) Deep Knowledge of Data Warehousing, ETL/ELT Architectures & Heavy Analytic Environments (Apache Beam, Hadoop, Spark, Hive) Responsibilities: Leading Customer-Facing AI Deployments across Europe ...

modern AWS production environments. The Technical Reality: We operate a pragmatic stack where Linear Regression remains vital for stability and baseline performance, while XGBoost and LLMs are used as responsible additions. We are looking for someone who knows when to use a simple linear model and when to deploy … Responsibilities Predictive Modelling (Linear & Non-Linear): You will build and maintain foundational Linear Regression models for credit, affordability, and fraud scoring, while developing advanced XGBoost models for deeper risk insights. You will mine data to find behavioural signals—such as spending volatility or income stability—that predict affordability, repayment ...