Algorithm Engineer, SRA - Promotion (2027 Graduate)

Shopee; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Shopee in Singapore is seeking a machine learning-focused professional to join the SRA Promotion team. The role centers on building scalable data products to promote the marketplace, analyzing large-scale user and item data, and delivering data-driven insights for campaign planning and personalization.

You will collaborate with product and engineering teams to deploy end-to-end ML pipelines, apply LLMs and agents, and evaluate campaigns using online/offline experiments to maximize impact.

Qualifications

• Bachelor’s degree or above in Computer Science, Engineering, Mathematics, Statistics, Biostatistics, or related fields.
• Proficiency in at least one programming language (e.g., Python, Golang, Scala) and Unix/Linux systems.
• Experience working with large datasets and complex data analysis using SQL, Python.
• Knowledge of optimization, classical machine learning (classification, regression, clustering), deep learning, and reinforcement learning.
• Good understanding of LLMs and agents, having practical project experience is a plus.
• Experience with TensorFlow/PyTorch, distributed data processing frameworks (e.g., Hadoop, Spark).
• Good communication skills with ability to explain technical content to stakeholders.
• Teamwork mindset and ability to collaborate with cross-functional teams.

Responsibilities

• Work closely with the promotion product team, business partners, and internal stakeholders to identify marketplace growth challenges, uncover actionable insights, and deliver practical, scalable solutions based on large-scale user and product data.
• Collaborate with product and engineering teams to design and build end-to-end machine learning pipelines to power data-driven decision-making for promotions and campaign planning.
• Apply cutting-edge AI technologies such as LLMs, Agents, and RL to improve efficiency of building e-commerce campaigns.
• Work on core solutions related to personalized recommendations, promotion and voucher configuration optimization, campaign budget planning, and product demand forecasting.
• Develop, iterate, and maintain machine learning models, including those based on deep learning, reinforcement learning, and multi-armed bandit frameworks, applied in areas such as recommendation, search, and ads ranking.
• Conduct rigorous online and offline evaluations, including A/B testing, to ensure model effectiveness and business impact.

Skills

Python

Golang

Scala

SQL

Unix/Linux

Communication

Education

Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Biostatistics, or related fields

Tools

TensorFlow/PyTorch

Hadoop

Spark

LLMs/Agents

Job description

About The Team
The mission of the SRA Promotion team is to build sustainable and scalable data products to promote the business and mission of Shopee marketplace by analyzing massive item and user related data, producing reliable predictive business insights and data-driven services, maximizing the effectiveness of marketing campaigns as well as providing personalized e-commerce experiences based on all-round item profiling and user profiling data and information. The team aims to utilise advanced AI technologies including recommender systems, AI agents, causal inference and operations research to continuously improve Shopee campaign efficiency and customer experience.

Job Description

• Work closely with the promotion product team, business partners, and internal stakeholders to identify marketplace growth challenges, uncover actionable insights, and deliver practical, scalable solutions based on large-scale user and product data.
• Collaborate with product and engineering teams to design and build end-to-end machine learning pipelines to power data-driven decision-making for promotions and campaign planning.
• Apply cutting-edge AI technologies such as LLMs, Agents, and RL to improve efficiency of building e-commerce campaigns.
• Work on core solutions related to personalized recommendations, promotion and voucher configuration optimization, campaign budget planning, and product demand forecasting.
• Develop, iterate, and maintain machine learning models, including those based on deep learning, reinforcement learning, and multi-armed bandit frameworks, applied in areas such as recommendation, search, and ads ranking.
• Conduct rigorous online and offline evaluations, including A/B testing, to ensure model effectiveness and business impact.

Requirements

• Bachelor’s degree or above in Computer Science, Engineering, Mathematics, Statistics, Biostatistics, or related fields.
• Proficiency in at least one programming language (e.g., Python, Golang, Scala) and Unix/Linux systems.
• Experience working with large datasets and complex data analysis using SQL, Python.
• Knowledge of optimization, classical machine learning (classification, regression, clustering), deep learning, and reinforcement learning.
• Good understanding of LLMs and agents, having practical project experience is a plus.
• Experience with TensorFlow/PyTorch, distributed data processing frameworks (e.g., Hadoop, Spark).
• Good communication skills with ability to explain technical content to stakeholders.
• Teamwork mindset and ability to collaborate with cross-functional teams.