Senior Data Scientist - Search

go-jek singapore pte. ltd.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

go-jek singapore pte. ltd. in Singapore seeks an experienced ML Engineer to design and optimize hybrid lexical–semantic retrieval pipelines powering GoFood and GoPay surfaces.

You will build embeddings, relevance signals, and multi-task ranking models leveraging real-time signals such as promotions and stock. The role requires a Master’s or higher in CS/ML/NLP, strong Python/C++, or Java, and hands-on experience with large-scale ranking or recommendation systems in consumer apps.

Qualifications

• Master’s degree or higher in Computer Science, Machine Learning, NLP, CV, or a related field.
• Hands-on experience building large-scale ranking or recommendation systems in consumer products.
• Familiarity with LLMs and/or LLVMs. Experience integrating them into search or recommendation pipelines.
• Demonstrated ability to innovate with new algorithms or tools and drive measurable impact, especially using LLMs/LLVMs.
• 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.

Responsibilities

• Design and optimise hybrid lexical–semantic retrieval pipelines 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 balancing conversion, merchant quality, and long-term user retention with real-time signals.
• Build personalised ranking layers and user behaviour models leveraging historical orders and contextual features.
• Engineer recommendation algorithms using collaborative filtering, graph-based methods, and sequence models for retrieval expansion.
• Advance embedding quality for multi-modal data and use LLMs to enhance structured knowledge.
• Incorporate structured metadata and knowledge-graph features into retrieval and ranking pipelines to improve semantic understanding.

Skills

Python

C++

Java

Ranking systems

LLMs

LLVMs

Product intuition

English communication

Self-motivation

Education

Master’s degree or higher in Computer Science, Machine Learning, NLP, CV, or a related field

Job description

What will you 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.

What you will need?

• 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.