Gotogroup5mo ago

Senior Machine Learning - Search

SingaporePermanentsenior

Data ScienceMachine LearningData & AI

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Overview

About the Role As a Senior Machine Learning Engineer – Search, you will play a pivotal role in shaping the intelligence behind GoFood and GoPay. You’ll design, build, and deploy cutting-edge search, recommendation, and monetization models that power on-demand and financial use cases across…

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About the Role

As a Senior Machine Learning Engineer – Search, you will play a pivotal role in shaping the intelligence behind GoFood and GoPay. You’ll design, build, and deploy cutting-edge search, recommendation, and monetization models that power on-demand and financial use cases across Indonesia.

In your first six months, you’ll help launch foundational platform capabilities and partner closely with business-facing data science teams to drive measurable business impact and elevate the user experience.

If you’re passionate about applying advanced algorithms to solve real-world problems at scale, this role is one of the highest-leverage opportunities in the company.

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.

Master’s degree or higher in Computer Science, Machine Learning, NLP, CV, or a related field; strong programming skills in Python, C++, or Java.

Hands-on experience building large-scale ranking or recommendation systems in consumer products (ecommerce, food delivery, rideshare, ads, streaming, social).

Familiarity with LLMs and/or LLVMs. Experience integrating them into search or recommendation pipelines is a strong plus.

Demonstrated ability to innovate with new algorithms or tools and drive measurable impact, especially making use of Large language Models (LLMs) and Large Language and Vision models (LLVMs) in search or recommendation modeling.

Strong product intuition and ability to reason from user behavior data and traffic patterns.

Good communication skills in English, both written and verbal.

Self-motivated, curious, and excited by the opportunity to build high-impact systems quickly.