Student Researcher (AI Foundation Model Infrastructure - Seed) - 2027 Start (PhD)

    Highlights

    Explore methods to improve efficiency, scalability, and reliability across areas such as training platforms, inference systems, compilers, and distributed systems. Research or internship experience related to large-scale systems, inference optimization, compilers, or performance optimization.

    Numbers & Facts

    LocationSeattle, WA

    Description

    About the team

    The Seed Infrastructures team oversees the distributed training, reinforcement learning framework, high-performance inference, and heterogeneous hardware compilation technologies for AI foundation models.

    Responsibilities

    • Conduct research on infrastructure and systems for large-scale models.
    • Explore methods to improve efficiency, scalability, and reliability across areas such as training platforms, inference systems, compilers, and distributed systems.
    • Design and prototype system components, algorithms, or frameworks.
    • Collaborate with the team to advance research directions.

    Minimum Qualifications

    • Currently pursuing a PhD in computer science, mathematics, engineering, or a related field.
    • Strong programming skills and solid foundation in algorithms, data structures, and systems, proficient in Python or C/C++.
    • Research or internship experience related to large-scale systems, inference optimization, compilers, or performance optimization.

    Preferred Qualifications

    • Strong problem-solving and engineering skills.
    • Ability to collaborate effectively in a research environment.

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