Machine Learning Engineer (Recommendation) - Global E-Commerce

ByteDance
Singapore
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: bachelorsSkills: ["Problem-solving","Communication","Teamwork","Eagerness to learn","Positive mindset"]

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.

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FursaFursa
ByteDance
ByteDance
1 month 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: 30 days agoStatus: Live
Reposted: similar role first listed 1 month ago

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
WebsiteLinkedIn