ByteDance

2 days ago

Machine Learning Engineer (Recommendation), Global E-Commerce Alliance

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 32 minutes agoStatus: Live

Job Summary

Build and design large-scale recommendation algorithms to model creators’ real-time interests and improve conversion efficiency. Optimize massive commodity relationship mining, ranking, recall, and GMV by analyzing creator and merchant behavior at scale. Develop scalable AI/ML models, including ETL for realtime unstructured data, run and debug experiments in production systems, and collaborate with relevant software platforms to support e-commerce growth for millions of merchants.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Build and design large-scale machine learning algorithms to model creators’ real-time interests and improve conversion efficiency.
•Optimize commodity relationship mining, ranking, and recall for product recommendations to improve overall platform GMV.
•Analyze creator and merchant behavior at scale to create targeted algorithm strategies that improve monetization efficiency and support industrial upgrading.
•Develop scalable and optimized AI/ML models, including ETL pipelines for realtime, unstructured data to deploy ML solutions.
•Run experiments on deployed models to evaluate performance and identify and resolve issues; collaborate with platforms and teams to deploy models.

Key Requirements

•Bachelor’s, Master’s, or PhD degree in Computer Science or a related field.
•Experience with C++ and Python.
•Proficiency in at least one Big Data tool (e.g., Hive SQL, Spark, MapReduce) and at least one Deep Learning tool (e.g., TensorFlow, PyTorch).
•Applied machine learning experience and familiarity with recommendation/ML algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, or Deep Neural Networks.
•Industry experience in personalized recommendation, online advertising, information retrieval, or related fields.

Experience:E-commercePersonalized recommendationOnline advertisingInformation retrieval

Education:

Skills:CommunicationCooperationExcellent learning abilityProblem-solving

Tech Stack:C++PythonHive SQLSparkMapReduceTensorFlowPyTorchCollaborative FilteringMatrix FactorizationFactorization MachinesWord2vecLogistic RegressionGradient Boosting TreesDeep Neural Networks

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 Alliance

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 32 minutes agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Build and design large-scale machine learning algorithms to model creators’ real-time interests and improve conversion efficiency.
•Optimize commodity relationship mining, ranking, and recall for product recommendations to improve overall platform GMV.
•Analyze creator and merchant behavior at scale to create targeted algorithm strategies that improve monetization efficiency and support industrial upgrading.
•Develop scalable and optimized AI/ML models, including ETL pipelines for realtime, unstructured data to deploy ML solutions.
•Run experiments on deployed models to evaluate performance and identify and resolve issues; collaborate with platforms and teams to deploy models.

Key Requirements

•Bachelor’s, Master’s, or PhD degree in Computer Science or a related field.
•Experience with C++ and Python.
•Proficiency in at least one Big Data tool (e.g., Hive SQL, Spark, MapReduce) and at least one Deep Learning tool (e.g., TensorFlow, PyTorch).
•Applied machine learning experience and familiarity with recommendation/ML algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, or Deep Neural Networks.
•Industry experience in personalized recommendation, online advertising, information retrieval, or related fields.

Experience:E-commercePersonalized recommendationOnline advertisingInformation retrieval

Education:

Skills:CommunicationCooperationExcellent learning abilityProblem-solving

Tech Stack:C++PythonHive SQLSparkMapReduceTensorFlowPyTorchCollaborative FilteringMatrix FactorizationFactorization MachinesWord2vecLogistic RegressionGradient Boosting TreesDeep Neural Networks

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