Machine Learning Engineer (User Growth & Intelligent Marketing) - Global E-Commerce Technology [...]

ByteDance; Singapore; On-site; SGD 70,000 - 95,000; Full time

Job summary

ByteDance in Singapore seeks an experienced professional for an E-commerce Algorithm role focused on recommendation systems and marketing strategies. The ideal candidate will have a Bachelor's degree in a technical field and at least 3 years of experience in user growth or intelligent marketing, with strong skills in C++, Python, and relevant Big Data and Deep Learning tools. Responsibilities include optimizing marketing algorithms and contributing to technical solutions that drive user engagement and growth.

Qualifications

• Experience in C++ and Python; at least one Big Data tool & one Deep Learning tool.
• Strong foundation in algorithms and data structures.
• At least 3 years of relevant experience.

Responsibilities

• Optimize global E-commerce growth and marketing algorithms.
• Establish a user lifecycle data and value system.
• Contribute to product and technical solutions for user growth engines.
• Optimize algorithms for new user recommendations.
• Improve marketing efficiency and drive e-commerce growth.

Skills

C++

Python

Big Data tools

Deep Learning tools

Strong coding skills

Communication

Teamwork

Education

Bachelor's degree or higher in Computer Science, Computer Engineering, Mathematics or related technical discipline

Tools

Hive SQL

Spark

TensorFlow

PyTorch

Job description

Job Code: A27971

About the Team

The E-commerce Recommendation and Marketing Algorithm team is responsible for algorithm and big data work on e-commerce innovation projects. Leveraging on our products, the team helps users discover and acquire great products, enriching their lives. In this team, we not only use recommendation and search algorithms to help users find items they are interested in but also employ risk control algorithms and intelligent platform governance algorithms to detect violations, ensuring a secure shopping experience. We build intelligent customer service technologies and large-scale product knowledge graphs to improve the efficiency of various transaction processes. Furthermore, we develop logistics and operations research algorithms to enhance supply chain efficiency, and we apply artificial intelligence to help merchants improve their operational capabilities. Our mission: To make high-quality products easily accessible, enabling everyone to enjoy a better life.

Responsibilities

• Participate in optimizing global E-commerce growth and marketing algorithms, including core capabilities such as user value modelling, personalized messaging, recommendations, and intelligent marketing.
• Establish a user lifecycle data and value system to address core pain points and business challenges related to e-commerce platform user growth.
• Contribute to the implementation of product and technical solutions for user growth engines, such as personalized push notifications/emails, recommendation handling, etc., to increase e-commerce DAU and penetration rates.
• Optimize algorithms related to recall/sorting for new user recommendations, improving the relevance of traffic source handling and the accuracy and diversity of new user recommendations.
• Optimize intelligent marketing algorithms, utilizing uplift models and operations research methods to improve marketing efficiency and drive e-commerce GMV growth.

Qualifications

Minimum Qualifications

• Bachelor's degree or higher in Computer Science, Computer Engineering, Mathematics or related technical discipline.
• Experience in C++ and Python; at least one of the Big Data tools (for example, Hive SQL, Spark, MapReduce) and at least one of the Deep Learning tools (for example, TensorFlow, PyTorch).
• Strong foundation in algorithms and data structures, with excellent coding skills.
• Strong learning ability, curiosity, and good communication and teamwork skills.
• At least 3 years of relevant experience in user growth or intelligent marketing.

Preferred Qualifications

• Candidates who have published papers in top AI conferences/journals or achieved notable results in ACM/Machine Learning competitions.
• Experience in recommendation systems, advertising, user growth, intelligent marketing, or related fields, with expertise in LTV estimation, uplift modelling, operations research, sequence modelling, or multi-scenario modelling optimization.