Machine Learning Engineer, Ranking & Retrieval

Overview

Build and improve machine learning models for classification, retrieval, ranking and personalisation in an agent-first mobile communication app.

What you'll do

• Develop and improve ML models for classification, retrieval, ranking and personalisation.
• Build classifiers and ranking models, optimising accuracy, precision, latency and inference cost.
• Improve search relevance and context retrieval using embeddings, hybrid search and reranking.
• Develop personalisation models using user behaviour and product data.
• Build evaluation pipelines, datasets and metrics to measure model quality and detect regressions.
• Train, fine-tune and deploy models using production ML pipelines.
• Monitor model performance, debug production issues and improve models based on evaluation results and user feedback.

What you'll need

• 3+ years of machine learning engineering experience, including deploying models to production.
• Strong Python programming skills and experience with PyTorch or JAX.
• Solid understanding of machine learning algorithms, model training and evaluation.
• Experience with classification, ranking, retrieval, recommendation or personalisation models.
• Experience working with embeddings, vector search or information retrieval systems.
• Experience building data pipelines, training workflows and model inference services.
• Ability to evaluate model performance using relevant metrics and experimentation.
• Understanding of trade-offs between model accuracy, latency, computational cost and reliability.

Nice to have

• Experience with transformer models, LLM fine-tuning or embedding models.
• Experience with hybrid search, reranking and retrieval evaluation.
• Experience with recommendation systems or personalisation in consumer applications.
• Experience with large-scale ML training or inference infrastructure.