Machine Learning Engineer

AI ML Senior Engineer to join our growing ML Engineering team. Youll work alongside data scientists, engineers, and product managers to develop, deploy, and operate robust ML systems that power key services across our Digital and Retail platforms.This role focuses on ML Ops and ML Platform development, helping us to scale and maintain production-ready ML workflows using modern cloud infrastructure and tools.Your responsibilities Develop and maintain ML pipelines for training, validation, deployment, and monitoring of models.Support scalable ML solutions across use cases like recommendations, forecasting, and automation.Work with tools like Airflow, Azure ML, and FastAPI to deliver production-ready systems.Automate model deployment workflows using CICD tools (e.g. GitHub Actions, Azure DevOps).Contribute to the reliability, observability, and performance of the ML platform.Collaborate with data scientists to productionise research code and models into scalable services.Help implement monitoring, alerting, and model drift detection using tools like NewRelic, Azure Monitor, and custom logging frameworks.Continuously improve and manage infrastructure using Terraform, Docker, and Fargate.Your ProfileEssential skillsknowledgeexperience Proven experience in ML Engineering, DevOps, or Data Engineering with exposure to ML lifecycle.Hands-on experience building or maintaining ML workflows or pipelines.Strong Python skills and experience with tools like MLflow, Scikit-learn, or PyTorch.Familiarity with cloud platforms (especially Azure, AWS).Good understanding of containerisation (Docker) and orchestration (e.g. Kubernetes).Exposure to CICD tools (GitHub Actions, Azure DevOps) and infrastructure-as-code (Terraform).Collaborative team player with excellent communication skills.Technical StackLanguages Python (primary), SQL, Bash Cloud Azure, AWSTools MLflow, Azure ML, Airflow, Docker, Fargate, FastAPIData Snowflake, Delta Lake, Redis, Azure Data LakeInfra Ops Terraform, GitHub Actions, Azure DevOps, Grafana, Azure MonitorDesirable skillsknowledgeexperience Knowledge of data platforms (e.g. Snowflake, Azure Data Lake).Experience deploying models as APIs (FastAPI, Azure Functions).Understanding of monitoring, model performance tracking, and observability best practices.Familiarity with orchestration tools like Airflow or Azure Data Factory