Graduate ML Engineer — Global E‑Commerce Recommendations

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

Job summary

ByteDance is seeking an innovative applied ML Engineer to contribute to large-scale e-commerce recommendation systems, live stream and short video recommendations. You will develop user interest models, design predictive ranking pipelines, and collaborate on end-to-end ML experiments in a fast-growing tech environment.

Ideal candidates have a strong CS background, hands-on ML experience, and proficiency in C++ or Python, with TensorFlow/PyTorch familiarity.

Qualifications

• Bachelor's degree in Software Development, Computer Science, Computer Engineering, or related field.
• Strong programming and problem-solving ability.
• Experience in applied machine learning with common algorithms.
• Experience with Deep Learning tools such as TensorFlow or PyTorch.
• Experience with C++ or Python.

Responsibilities

• Participate in building large-scale E-commerce recommendation algorithms and systems.
• Build long and short term user interest models and analyze data to extract insights.
• Design, develop, evaluate and iterate on predictive models for candidate generation and ranking.
• Build supporting/debugging tools as needed.
• Support production of scalable and optimized ML models.
• Process large volumes of real-time, unstructured data for AI/ML solutions.
• Run experiments to test deployed models and resolve issues.
• Collaborate in a team and apply statistics, scripting and programming knowledge.
• Work with platforms where models are deployed.

Skills

Programming

ML experience

Deep Learning

C++/Python

TensorFlow/PyTorch

Bachelor's degree

Education

Bachelor's degree in CS/SE/related

Master's degree (preferred)

Tools

TensorFlow

PyTorch

C++

Python

Job description

ByteDance is seeking an innovative applied ML Engineer to contribute to large-scale e-commerce recommendation systems, live stream and short video recommendations. You will develop user interest models, design predictive ranking pipelines, and collaborate on end-to-end ML experiments in a fast-growing tech environment.

Ideal candidates have a strong CS background, hands-on ML experience, and proficiency in C++ or Python, with TensorFlow/PyTorch familiarity.