Member of Technical Staff, Machine Learning

Role overview Build and improve machine learning capabilities for a consumer communication product, helping it retrieve useful context, rank results, and adapt to user behaviour. The position combines hands-on model development with evaluation, deployment, and ongoing production performance work.

Responsibilities - Develop models for classification, retrieval, ranking, and personalisation. - Improve search and context retrieval using embeddings, vector search, hybrid approaches, and reranking. - Build classifiers and ranking systems while tuning for quality, precision, latency, and inference cost. - Create datasets and evaluation pipelines to measure model quality and identify regressions. - Train, fine-tune, and deploy models through production ML workflows. - Monitor deployed models, diagnose issues, and use metrics and user feedback to guide updates.

Requirements - Three or more years of machine learning engineering experience, including shipping models to production. - Strong Python skills and experience using PyTorch or JAX. - Solid grasp of model training, evaluation, and core machine learning methods. - Experience with at least one of classification, ranking, retrieval, recommendation, or personalisation. - Experience with embeddings, vector search, or information retrieval systems. - Ability to build data and inference workflows, select suitable evaluation metrics, and weigh accuracy against latency, compute cost, and reliability.

Nice to have - Experience with transformer architectures, fine-tuning language models, or embedding models. - Familiarity with hybrid search, reranking, and retrieval evaluation. - Consumer recommendation or personalisation experience. - Experience supporting ML training or inference at large scale.