ML Engineer

Responsibilities

• 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 Qualifications:
• 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 Py. Torch, Num. Py, 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