Research Engineer - Multimodal Training Infrastruc
Full-time
ByteDance
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.
Vacancy posted 5 days ago
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