E-commerce ML Engineer: Next-Gen Recommendation Systems

Pangleglobal; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

Pangleglobal is hiring for a PhD-qualified ML/DS professional to develop large-scale e-commerce recommendation algorithms. You will work on live stream and short video suggestions, using real-time data pipelines and advanced models to improve user engagement and conversion rates.

You will collaborate with a team of applied ML engineers and data scientists, building scalable ML solutions, evaluating performance, and iterating to achieve business impact. Availability by end of 2026 is requested.

Qualifications

• PhD in Software Development, Computer Science, or related technical discipline.
• Strong programming and problem-solving ability.
• Experience in applied machine learning with common algorithms (e.g., CF, Matrix Factorization, DFM, Word2vec, LR, GB Trees, DNNs).
• Experience with Deep Learning tools such as TensorFlow/PyTorch.
• Experience with at least one programming language like C++/Python or equivalent.

Responsibilities

• Participate in building large-scale e-commerce recommendation algorithms and systems (10M–100M users).
• Build long- and short-term user interest models from large data.
• Design, develop, evaluate and iterate on predictive models for candidate generation and ranking.
• Design and build supporting/debugging tools as needed.
• Support production of scalable and optimized ML models.
• Focus on extracting, transforming and loading large volumes of real-time data.
• Run experiments to test performance and fix issues.
• Collaborate in a team setting using statistics, scripting and programming languages.

Skills

Programming

Problem solving

Applied ML

Education

PhD in CS/Software Eng

Tools

TensorFlow/PyTorch

C++/Python

Job description

Pangleglobal is hiring for a PhD-qualified ML/DS professional to develop large-scale e-commerce recommendation algorithms. You will work on live stream and short video suggestions, using real-time data pipelines and advanced models to improve user engagement and conversion rates.

You will collaborate with a team of applied ML engineers and data scientists, building scalable ML solutions, evaluating performance, and iterating to achieve business impact. Availability by end of 2026 is requested.