Senior Recommender Systems ML Engineer (E-commerce)

TIKTOK PTE. LTD.; Singapore; Sur place; SGD 120 000 - 190 000; Plein temps

Résumé du poste

TikTok Pte. Ltd. is seeking a skilled engineer to advance large-scale e-commerce and content recommendation systems. You will design and optimize models spanning products, videos, and live streams across multiple countries, applying deep learning, transfer learning, and multi-task learning techniques.

The role involves data mining, model evaluation, and experimentation to boost content quality and system performance. Collaboration with ML and data teams is essential in a fast-paced environment.

Qualifications

• 3+ years of work experience in related field.
• Strong in data structures and algorithms with excellent problem-solving ability and programming skills.
• Experience in applied machine learning with algorithms such as collaborative filtering, matrix factorization, factorization machines, Word2vec, logistic regression, gradient boosting trees, or deep neural networks.

Responsabilités

• Work on recommendation systems for products, short videos, and live streams across multiple countries.
• Optimize e-commerce recommendation models at large scale using deep learning, transfer learning, or multi-task learning.
• Data mining and analysis to improve quality of recommended contents.

Connaissances

Data structures & algorithms

Applied machine learning

Recommender systems

Big data processing

Communication & teamwork

Outils

C++

Python

Hive/Spark/MapReduce

TensorFlow/PyTorch

Description du poste

TikTok Pte. Ltd. is seeking a skilled engineer to advance large-scale e-commerce and content recommendation systems. You will design and optimize models spanning products, videos, and live streams across multiple countries, applying deep learning, transfer learning, and multi-task learning techniques.

The role involves data mining, model evaluation, and experimentation to boost content quality and system performance. Collaboration with ML and data teams is essential in a fast-paced environment.