Hybrid ML Engineer — London, Scale Predictive Platform

Xantura Limited; Greater London; Hybrid; GBP 50.000 - 70.000; Vollzeit

Benefits dieser Stelle

Competitive salary

Private medical insurance

Pension scheme

Flexible hours

25 days annual leave

Cycle to work

Zusammenfassung

Xantura Limited is seeking a Machine Learning Engineer to join the Platform Delivery team in London. You will own and advance a scalable predictive modelling platform that supports housing, health, and other social domains.

The role requires 3+ years of ML engineering experience, strong Python and ML library skills, and hands-on deployment of containerised systems using Kubernetes and FastAPI. The position is hybrid, with 1-2 days in the office weekly.

Qualifikationen

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field or equivalent experience.
• 3+ years of professional ML Engineer experience.
• Strong Python programming and production experience.
• Experience building data/ML pipelines with orchestration tools (Dagster, Airflow, Prefect).
• Hands-on experience with ML libraries (PyTorch, scikit-learn, XGBoost/LightGBM).
• Experience deploying containerised systems (APIs via FastAPI; Kubernetes).

Aufgaben

• Own and advance a predictive modelling platform that scales across problem types and tenants.
• Run structured experiments to bring promising techniques into production safely.
• Build robust evaluation pipelines, training datasets, and model infrastructure for continuous improvement of NLP & predictive analytics.
• Ensure responsible AI deployment with ethical and regulatory considerations.

Kenntnisse

Python

Machine Learning

Model deployment

NumPy/Pandas

PyTorch

scikit-learn

XGBoost/LightGBM

Kubernetes

FastAPI

APIs

HuggingFace

Ausbildung

Bachelor’s or Master’s degree in CS/ML or related field

Tools

Dagster

Airflow

Prefect

Docker

Kubernetes

Jobbeschreibung

Xantura Limited is seeking a Machine Learning Engineer to join the Platform Delivery team in London. You will own and advance a scalable predictive modelling platform that supports housing, health, and other social domains.

The role requires 3+ years of ML engineering experience, strong Python and ML library skills, and hands-on deployment of containerised systems using Kubernetes and FastAPI. The position is hybrid, with 1-2 days in the office weekly.