- Deploy ML models and AI pipelines from PoC through to scalable, reliable production, via CI/CD and orchestration

- Implement monitoring and maintenance strategies for deployed models

- Optimise models for inference speed and resource efficiency (TensorRT, OpenVINO, ONNX, pruning, quantisation)

- Perform data collection, cleaning and feature engineering to prepare datasets for training

- Collaborate with data scientists, engineers and product managers; maintain clear documentation

- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, AI or related field

- 5-9 years of relevant experience

- Proficiency in Python and libraries such as PyTorch, NumPy, Pandas and Scikit-learn

- Knowledge of model deployment/containerisation (Docker, Kubernetes) and SQL/NoSQL databases

- Familiarity with a cloud platform and MLOps tooling (MLflow, ClearML, etc.); edge deployment experience a plus