Machine Learning Engineer

What you’ll be doing

Model Development:

Design, train, and optimise machine learning models for user personalisation, including recommendation systems, ranking models, user segmentation, and content understanding, with a strong focus on TensorFlow-based development.

Data Pipeline Engineering:

Build and maintain scalable data pipelines to support feature engineering and model training across large structured and unstructured datasets, leveraging cloud‑native tooling.

Production Deployment:

Deploy, monitor, and maintain ML models in production environments, including cloud‑based model serving on GCP. Ensure high availability, strong performance, and continuous model relevance.

Experimentation:

Lead A/B testing and offline experimentation to evaluate model performance and guide ongoing improvement.

Cross‑Functional Collaboration:

Work closely with engineering, product, data, and research teams to ensure ML solutions align with product and business goals.

Research & Innovation:

Stay informed on advances in machine learning, deep learning, and personalisation, and evaluate their integration into existing systems.

What you'll bring

• End‑to‑end experience ...