ByteDance

2 days ago

Machine Learning Engineer (Recommendation) - Global E-Commerce

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Build and improve large-scale e-commerce recommendation systems across products, short videos, and live streams for global scenarios. Optimize models at massive scale using deep learning, transfer learning, and multi-task learning, and use data mining to enhance recommendation quality. Research and develop new approaches for diversity, discovery, and cold-start challenges, then run and debug experiments for deployed AI/ML models and supporting data pipelines.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Work on e-commerce recommendation systems spanning products, short videos, and live streams, unifying models across diverse scenarios and goals across multiple countries.
•Optimize recommendation models at massive scale using deep learning, transfer learning, and multi-task learning techniques.
•Perform data mining and analysis to improve the quality of recommended content.
•Conduct research to optimize recommendation circulation, including diversity/new discovery and cold-start for new users/items and discovery of high-quality products/live streamers.
•Develop and support scalable, optimized AI/ML models, including building pipelines for large volumes of real-time unstructured data and running experiments to validate and debug deployed model performance.

Key Requirements

•Bachelor's degree in Computer Science or a related field.
•Strong data structures/algorithms and problem-solving with solid programming skills.
•Applied machine learning experience with recommendation algorithms such as collaborative filtering, matrix factorization, factorization machines, Word2vec, logistic regression, gradient boosting trees, and deep neural networks.
•Experience with core recommendation system components (recall, sort, reranking, cold-start) and mainstream recommendation models.
•Experience with C++ and Python plus at least one Big Data tool (e.g., Hive SQL, Spark, MapReduce) and at least one deep learning tool (e.g., TensorFlow, PyTorch).

Experience:E-commerceRecommendation systemsMachine learningOnline advertisingInformation retrieval

Education:Bachelor's

Skills:Problem-solvingCommunicationTeamworkEagerness to learnPositive mindset

Tech Stack:C++PythonHiveSparkMapReduceTensorFlowPyTorchCollaborative FilteringMatrix FactorizationFactorization MachinesWord2vecLogistic RegressionGradient Boosting TreesDeep Neural NetworksDeep LearningTransfer LearningMulti-task LearningTensorflow/Pytorch

Company Brief

ByteDance

Develops consumer internet and content platforms, including TikTok and other apps for short-form video, news, and entertainment. It also builds advertising, commerce, and creator tools that connect audiences, brands, and publishers across global markets.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn

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ByteDance

2 days ago

Machine Learning Engineer (Recommendation) - Global E-Commerce

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Work on e-commerce recommendation systems spanning products, short videos, and live streams, unifying models across diverse scenarios and goals across multiple countries.
•Optimize recommendation models at massive scale using deep learning, transfer learning, and multi-task learning techniques.
•Perform data mining and analysis to improve the quality of recommended content.
•Conduct research to optimize recommendation circulation, including diversity/new discovery and cold-start for new users/items and discovery of high-quality products/live streamers.
•Develop and support scalable, optimized AI/ML models, including building pipelines for large volumes of real-time unstructured data and running experiments to validate and debug deployed model performance.

Key Requirements

•Bachelor's degree in Computer Science or a related field.
•Strong data structures/algorithms and problem-solving with solid programming skills.
•Applied machine learning experience with recommendation algorithms such as collaborative filtering, matrix factorization, factorization machines, Word2vec, logistic regression, gradient boosting trees, and deep neural networks.
•Experience with core recommendation system components (recall, sort, reranking, cold-start) and mainstream recommendation models.
•Experience with C++ and Python plus at least one Big Data tool (e.g., Hive SQL, Spark, MapReduce) and at least one deep learning tool (e.g., TensorFlow, PyTorch).

Experience:E-commerceRecommendation systemsMachine learningOnline advertisingInformation retrieval

Education:Bachelor's

Skills:Problem-solvingCommunicationTeamworkEagerness to learnPositive mindset

Company Brief

ByteDance

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Established Company

Headquarters: Beijing, China

Founded: 2012

Website LinkedIn