9 hours ago

Machine Learning Engineer (Recommendation) - TikTok e-Commerce

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 9 hours agoStatus: Live

Job Summary

Build and improve large-scale e-commerce recommendation systems that unify diverse content signals (products, short videos, live streams) across multiple countries. Optimize models at massive scale using deep learning, transfer learning, and multi-task learning, and use data mining to enhance recommendation quality. Research topics like diversity, new discovery, cold-start, and high-quality discovery, while developing state-of-the-art algorithms and scalable ML pipelines. Experiment, debug, and partner with deployed software platforms.

Location: Singapore

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Work on e-commerce recommendation systems using a unified recommendation model across heterogeneous scenarios/goals and multiple countries.
•Optimize e-commerce recommendation models at massive scale using deep learning, transfer learning, and multi-task learning.
•Perform data mining and analysis to improve the quality of recommended content.
•Conduct research to improve recommendation circulation, including diversity, new discovery, cold-start for new users/items, and discovery of high-quality products/live streamers.
•Develop and deploy scalable, optimized AI/ML models by building pipelines for extracting, transforming, and loading large volumes of real-time unstructured data; run experiments and resolve model deployment bugs.

Key Requirements

•At least 3 years of work experience in a related field.
•Strong in data structures and algorithms, with excellent problem-solving and programming skills.
•Applied machine learning experience with recommender 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 including recall, sort, reranking, and cold-start, with understanding of mainstream recommendation models.
•Proficiency in C++ and Python, plus experience with Big Data tools (e.g., Hive SQL, Spark, MapReduce) and deep learning tools (e.g., TensorFlow, PyTorch).

Experience:3+ years

Skills:CommunicationTeamworkProblem-solvingEagerness to learnPositive mindset

Tech Stack:C++PythonHiveSQLSparkMapReduceTensorFlowPyTorchDeep learningTransfer learningMulti-task learningCollaborative FilteringMatrix FactorizationFactorization MachinesWord2vecLogistic RegressionGradient Boosting TreesDeep Neural Networks

Company Brief

TikTok

Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn

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TikTok

9 hours ago

Machine Learning Engineer (Recommendation) - TikTok e-Commerce

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 9 hours agoStatus: Live

Job Summary

Location: Singapore

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Work on e-commerce recommendation systems using a unified recommendation model across heterogeneous scenarios/goals and multiple countries.
•Optimize e-commerce recommendation models at massive scale using deep learning, transfer learning, and multi-task learning.
•Perform data mining and analysis to improve the quality of recommended content.
•Conduct research to improve recommendation circulation, including diversity, new discovery, cold-start for new users/items, and discovery of high-quality products/live streamers.
•Develop and deploy scalable, optimized AI/ML models by building pipelines for extracting, transforming, and loading large volumes of real-time unstructured data; run experiments and resolve model deployment bugs.

Key Requirements

•At least 3 years of work experience in a related field.
•Strong in data structures and algorithms, with excellent problem-solving and programming skills.
•Applied machine learning experience with recommender 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 including recall, sort, reranking, and cold-start, with understanding of mainstream recommendation models.
•Proficiency in C++ and Python, plus experience with Big Data tools (e.g., Hive SQL, Spark, MapReduce) and deep learning tools (e.g., TensorFlow, PyTorch).

Experience:3+ years

Skills:CommunicationTeamworkProblem-solvingEagerness to learnPositive mindset

Company Brief

TikTok

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn