Machine Learning Engineer

- Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications - Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements - Transition validated experiments into production-ready solutions, working closely with other engineers on deployment and monitoring - Build and optimise ML pipelines using AWS services and experiment tracking tools - Develop and integrate LLM-powered solutions for tracing, evaluation, and production monitoring - Implement robust experiment tracking, model versioning, and reproducibility practices with full audit trails - Design feature engineering approaches and contribute to feature store development - Support production models through monitoring, performance analysis, and continuous improvement - Apply responsible AI practices, including model explainability and fairness assessment - Present experiment findings and production outcomes to stakeholders, articulating operational and strategic value - Mentor junior colleagues and share learnings across the team