Machine Learning Engineer Graduate (Global E-Commerce, Recommendation) - 2027 Start (PhD)

TikTok
Singapore
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: phdSkills: ["Problem-solving","Experimentation","Collaboration","Programming"]

Build and scale e-commerce recommendation algorithms and systems across commodity, live stream, and short-video experiences. Develop long- and short-term user interest models and predictive ranking systems (e.g., CTR and conversion rate), including real-time data pipelines, feature engineering, and model optimization. Support production ML deployments, create debugging tools, run experiments to improve performance, and help deploy AI solutions from large volumes of real-time unstructured data.

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FursaFursa
TikTok
TikTok
1 day ago

Machine Learning Engineer Graduate (Global E-Commerce, Recommendation) - 2027 Start (PhD)

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 12 hours agoStatus: Live

Job Summary

Build and scale e-commerce recommendation algorithms and systems across commodity, live stream, and short-video experiences. Develop long- and short-term user interest models and predictive ranking systems (e.g., CTR and conversion rate), including real-time data pipelines, feature engineering, and model optimization. Support production ML deployments, create debugging tools, run experiments to improve performance, and help deploy AI solutions from large volumes of real-time unstructured data.
Location: Singapore
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Graduate level

Key Responsibilities

  • •Participate in building large-scale (billion-level) e-commerce recommendation algorithms and systems for commodity, live stream, and short-video recommendations.
  • •Build user interest models and analyze large datasets to design algorithms that capture users’ latent interests.
  • •Design, develop, evaluate, and iterate predictive models for candidate generation and ranking, including real-time data pipelines, feature engineering, and model optimization.
  • •Design and build supporting/debugging tools as needed for deployed models.
  • •Run experiments to test performance of deployed models and identify and resolve bugs.

Key Requirements

  • •Be completing or have recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
  • •Strong programming and problem-solving skills.
  • •Applied machine learning experience, including familiarity with recommendation algorithms (e.g., collaborative filtering, matrix factorization, factorization machines, Word2vec, logistic regression, gradient boosting trees, deep neural networks, Wide & Deep).
  • •Experience with deep learning frameworks/tools such as TensorFlow or PyTorch.
  • •Experience with at least one programming language such as C++ or Python.
Experience:E-commerceRecommendation systemsOnline advertisingInformation retrievalNatural language processingLarge-scale data miningData mining
Education:PhD / Doctorate in PhD
Skills:Problem-solvingExperimentationCollaborationProgramming
Tech Stack:TensorFlowPyTorchC++PythonDeep neural networksWord2vecCollaborative filteringMatrix factorizationFactorization machinesLogistic regressionGradient boosting treesWide and deepReal-time data pipelinesFeature engineeringCTR predictionConversion rate predictionKaggle

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
WebsiteLinkedIn