Research Scientist, ML Recommendation Systems, Applied Machine Learning Team

ByteDance
San Jose
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: bachelorsSkills: ["Problem-solving","Cross-functional collaboration"]

Drive innovation for recommendation systems by building and scaling machine learning models used across TikTok, Douyin, and other products. Research and apply multi-modal techniques and long-term user behavior signals, including reinforcement learning for personalization. Partner with infrastructure to co-design high-performance, low-latency model architectures and deploy end-to-end ML solutions that measurably improve user experience.

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ByteDance
ByteDance
1 month ago

Research Scientist, ML Recommendation Systems, Applied Machine Learning Team

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 31 days agoStatus: Live
Reposted: similar role first listed 1 month ago

Job Summary

Drive innovation for recommendation systems by building and scaling machine learning models used across TikTok, Douyin, and other products. Research and apply multi-modal techniques and long-term user behavior signals, including reinforcement learning for personalization. Partner with infrastructure to co-design high-performance, low-latency model architectures and deploy end-to-end ML solutions that measurably improve user experience.
Location: San Jose
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build and scale machine learning models for recommendation systems.
  • •Research and apply multi-modal techniques using text, image, and video to model content and user preferences.
  • •Develop long-term user behavior modeling strategies, including reinforcement learning for personalization.
  • •Partner with infrastructure to co-design and optimize next-generation recommendation model architectures for high-performance, low-latency, cost-efficient training and inference at scale.
  • •Collaborate with product, engineering, and design teams to test, deploy, and validate end-to-end solutions that enhance user experience.

Key Requirements

  • •Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field; Ph.D. preferred.
  • •At least 5 years of experience with programming languages such as Python or C++ and deep learning frameworks like PyTorch or TensorFlow.
  • •Expertise designing, building, and scaling machine learning models for recommendation systems.
  • •Hands-on experience with modern deep learning techniques including Transformers, Large Language Models (LLMs), and multi-modal learning.
  • •Experience building and deploying end-to-end ML pipelines in production; publications in peer-reviewed conferences such as NeurIPS, ICML, ICLR, KDD, RecSys, or WWW.
Experience:5+ years
Education:Bachelor's in Computer Science, Computer Engineering, or a related technical field
Skills:Problem-solvingCross-functional collaboration
Tech Stack:PythonC++PyTorchTensorFlowTransformersLarge Language Models (LLMs)Multi-modal learningReinforcement learning

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