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Research Engineer - Multimodal Training Infrastruc

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Research Engineer - Multimodal Training Infrastruc in USA

  • ByteDance
  • Full time
  • Email
  • San Jose, CA

Responsibilities

  • Conduct research and development on large-scale infrastructure for training foundation models, multimodal LLMs, and image/video generation models.
  • Design and optimize distributed training strategies, including data, model, pipeline, and expert parallelism.
  • Improve computation, communication, throughput, networking, scheduling, and GPU memory management across the training stack.
  • Research reliability and resilience techniques including fast checkpointing, fault tolerance, and failure diagnosis.
  • Analyze performance bottlenecks in exascale training systems and develop data-driven optimization methods.
  • Translate research ideas into scalable, production-ready infrastructure solutions.

Requirements

  • Deep expertise in large-scale distributed training of LLMs and multimodal models.
  • Strong systems research background with demonstrated ability to design, build, and optimize large-scale ML systems.
  • Proven experience with data, model, pipeline, and expert parallelism and performance optimization on large GPU clusters.
  • Strong programming skills and hands-on experience implementing production-grade ML systems or infrastructure.
  • Solid understanding of algorithm–system co-design and cross-layer optimization for training efficiency, scalability, and reliability.

ByteDance

ByteDance is a global incubator of platforms at the cutting edge of commerce, content, entertainment and enterprise services - over 2.5bn people interact with ByteDance products including TikTok. Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This...

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