About the Role
As a Machine Learning Engineer specializing in Search & Recommendations, you will be instrumental in designing and optimizing advanced retrieval and ranking systems for GoFood and GoPay. Your work will directly impact user experience by improving the precision and recall of search results, personalizing recommendations, and enhancing the overall relevance of content presented to millions of users.
What You Will Do
- Design and optimise hybrid lexical–semantic retrieval pipelines (e.g., BM25, dense vectors, HNSW/LSH, generative retrieval) to improve precision and recall across GoFood and GoPay surfaces.
- Build high-quality embeddings and relevance signals that capture user intent, cuisine and dish semantics, geolocation, delivery constraints, price sensitivity, and promotions.
- Develop multi-task deep ranking models that balance conversion, diversity, merchant quality, and long-term user retention, integrating real-time signals such as promotions, surge, and stock availability.
- Build personalised ranking layers and user behaviour models leveraging historical orders, preferences, and contextual features.
- Engineer recommendation algorithms using collaborative filtering, graph-based methods, and sequence models for retrieval expansion (e.g., Q2Q2I, Q2I2I, U2I), including for cold-start merchants and new dishes.
- Advance embedding quality for multi-modal data (text, images, behavioural signals) and use LLMs to enhance structured knowledge (taxonomy tagging, dish attributes, dietary labels).
- Incorporate structured metadata, taxonomy signals, and knowledge-graph features into retrieval and ranking pipelines to improve semantic understanding and consistency.