Machine Learning Engineer

Overview

Machine Learning Engineer on a contract basis, offering a competitive pay rate. Key skills include TensorFlow, Python, GCP, and experience with ML lifecycle management. Familiarity with recommender systems and A/B testing is essential.

Location: United Kingdom

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 across the ML lifecycle: model development, training, deployment, monitoring, and continuous maintenance.
• Strong proficiency in Python and ML frameworks, with expertise in TensorFlow (and experience with PyTorch).
• Experience with GCP machine learning and data services (e.g., Vertex AI, Dataflow, BigQuery, AI Platform, Pub/Sub).
• Hands on experience with ML training frameworks such as TFX or Kubeflow Pipelines, and model serving technologies like TensorFlow Serving, Triton, or TorchServe.
• Background working with large scale batch and real time data processing systems.
• Strong understanding of recommender systems, ranking models, and personalisation algorithms.
• Familiarity with Generative AI and its use in production environments.
• Strong communication skills and analytical problem solving abilities.

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