Machine Learning System Engineer - Data AML - Soaring Star Talent Program

ByteDance
Singapore
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningEducation: phdSkills: ["Logical analysis","Collaboration","Communication","Self-motivation","Technical documentation"]

Build large-scale multimodal recommendation and training/inference systems for the Data AML platform, supporting ByteDance businesses like Douyin, Toutiao, and Xigua Video. Work on research and engineering co-design for multimodal co-training, ultra-large-scale (7B/13B) parameter models, longer sequence end-to-end methods, and high-performance inference/training engines using PyTorch. Collaborate on cloud-native infrastructure (including Kubernetes) and efficient deployment on heterogeneous hardware for next-gen AI systems.

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FursaFursa
ByteDance
ByteDance
1 month ago

Machine Learning System Engineer - Data AML - Soaring Star Talent Program

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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 large-scale multimodal recommendation and training/inference systems for the Data AML platform, supporting ByteDance businesses like Douyin, Toutiao, and Xigua Video. Work on research and engineering co-design for multimodal co-training, ultra-large-scale (7B/13B) parameter models, longer sequence end-to-end methods, and high-performance inference/training engines using PyTorch. Collaborate on cloud-native infrastructure (including Kubernetes) and efficient deployment on heterogeneous hardware for next-gen AI systems.
Location: Singapore
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning

Key Responsibilities

  • •Design and develop high-performance multimodal inference engines and multimodal training frameworks based on PyTorch.
  • •Develop and refine large-scale multimodal recommendation systems, including representation and co-training approaches.
  • •Explore scalable end-to-end recommendation methods using algorithm-engineering co-design for long sequences.
  • •Apply heterogeneous hardware to multimodal recommendation systems for improved performance.
  • •Contribute to algorithmic and system research such as recommendation-advertising multimodal co-training architectures, Sparse Mixture of Experts (Sparse MOE), Memory Network, and hybrid precision techniques.

Key Requirements

  • •Hold a doctoral degree, preferably in Computer Science, Software Engineering, or a related field.
  • •Proficient in one or more programming languages (C/C++/Go/Python/Java) working in a Linux environment.
  • •Deep understanding of distributed system principles, including designing, developing, and maintaining large-scale distributed systems.
  • •Strong logical analysis skills to abstract and decompose complex business logic, with a collaborative team spirit.
  • •Good technical documentation habits, including timely writing and updating of work processes and technical docs.
Experience:Distributed systemsCloud-nativeMachine learning infrastructureAI InfrastructureHigh-performance computingMultimodal recommendation
Education:PhD / Doctorate in Computer Science, Software Engineering (preferred)
Skills:Logical analysisCollaborationCommunicationSelf-motivationTechnical documentation
Tech Stack:CC++GoPythonJavaLinuxPyTorchTensorFlowMXNetKubernetesDjangoFlaskVolcano EngineGPUAcceleratorsNetworking

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