Senior Machine Learning Engineer

- Own the end-to-end delivery of production ML solutions in collaboration with data scientists and product teams - Design and build model pipelines for training, validation, and deployment using modern tooling (e.g. MLflow, Kubernetes, Airflow) - Contribute hands-on code to model packaging, deployment, and lifecycle automation - Build systems that monitor model performance, drift, and operational health in real time - Support both batch and real-time ML workloads depending on use case requirements - Define and promote best practices for reproducibility, testing, CI/CD, and model observability - Help evolve our internal ML platform to support experimentation, governance, and collaboration - Develop shared tools and libraries that accelerate safe, efficient, and scalable ML development - Work closely with data scientists to productionise experimental models and turn prototypes into robust services - Act as a technical mentor and code reviewer for other engineers and contributors - Provide architectural guidance across multiple ML projects and technical design sessions - Contribute to a culture of engineering excellence, collaboration, and learning - Stay up to date on emerging tools and approaches in MLOps and applied AI - Support responsible AI practices by contributing to explainability, auditability, and fairness initiatives in ML systems