Member of Technical Staff, Machine Learning

Job Scope Own the ML pipelines for training, inference and deployment, and keep them running smoothly. Use embeddings, hybrid search and re-ranking techniques to raise the quality of search results and context retrieval. Monitor how models behave in production, resolve issues and release improvements driven by user feedback.

Adapt or fine-tune existing models when there is enough data to support it. Develop models that personalise the user experience based on behaviour, with privacy built in. Create labelled datasets, evaluation pipelines and metrics to track model quality over time.

Design and enhance models for classification, ranking, retrieval and personalisation tasks. Build lean classifiers and tune them for accuracy, precision, speed and cost.

Track record of taking ML models from development into production. Clear understanding of experimentation, model evaluation and performance measurement. Practical background in classification, ranking, retrieval, recommender systems or personalisation.

Writes production-grade code and is comfortable handling real-world data. In-depth knowledge of machine learning and modern neural network architectures. Good judgement in balancing model quality against latency, cost and reliability.

Takes ownership and enjoys solving difficult problems. Tech Stack PyTorch / JAX Inference pipelines and production ML systems Python Ranking models, embeddings and vector search We regret that only shortlisted candidates will be notified.