Machine Learning Engineer, E-commerce Governance Algorithms

ByteDance
Seattle
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 3+ yearsSkills: ["Communication","Cross-functional collaboration","Stakeholder influence","Problem-solving"]

Build AI systems for e-commerce governance and experience, combating fraud and low-quality listings while improving delivery reliability and logistics performance. Work on graph-powered risk networks, LLM-based multi-modal cross-modal fusion, and time-series forecasting for operational metrics like delays and cancellations. Develop multi-task models (MMoE), causal inference frameworks, and optimize LLM reasoning (DPO/GRPO) to improve seller compliance, user trust, and supply chain efficiency.

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FursaFursa
ByteDance
ByteDance
1 month ago

Machine Learning Engineer, E-commerce Governance Algorithms

✓ 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 AI systems for e-commerce governance and experience, combating fraud and low-quality listings while improving delivery reliability and logistics performance. Work on graph-powered risk networks, LLM-based multi-modal cross-modal fusion, and time-series forecasting for operational metrics like delays and cancellations. Develop multi-task models (MMoE), causal inference frameworks, and optimize LLM reasoning (DPO/GRPO) to improve seller compliance, user trust, and supply chain efficiency.
Location: Seattle
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build graph-powered risk networks to identify similar product clusters and high-risk seller/creator groups to reduce false advertising incidents.
  • •Develop LLM-based multi-modal systems with cross-modal fusion to detect false advertising and low-quality products, and deploy AI suggestions to improve seller compliance.
  • •Lead time-series forecasting for logistics performance metrics such as delivery delays and cancellation rates to improve the e-commerce experience.
  • •Develop multi-task models using MMoE and dynamic loss functions to improve platform product, service, and logistics health.
  • •Optimize LLM reasoning (DPO/GRPO), build heterogeneous relationship graphs, and create unified time-series forecasting models to predict inventory shortages and demand surges.

Key Requirements

  • •Proficient in Python/C++ and machine learning frameworks (PyTorch/TensorFlow).
  • •Deep experience with graph neural networks, time series analysis, or LLMs.
  • •3+ years in anti-fraud, prediction/forecasting, e-commerce governance, or related fields.
  • •Track record of delivering AI solutions with measurable business impact.
  • •Strong communication skills to collaborate cross-functionally and influence stakeholders.
Experience:3+ yearsAnti-fraudE-commercePrediction/forecasting
Skills:CommunicationCross-functional collaborationStakeholder influenceProblem-solving
Tech Stack:PythonC++PyTorchTensorFlowGraph Neural NetworksTime Series PredictionLarge Language Models (LLM)Multi-Objective OptimizationMulti-modal systemsCross-modal fusionMMoEDynamic loss functionsCausal inferenceDPOGRPOTabular data modelingHeterogeneous graphs

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