The Seed Infrastructures team oversees the distributed training, reinforcement learning framework, high-performance inference, and heterogeneous hardware compilation technologies for AI foundation models.
Responsibilities
Contribute to infrastructure and systems for large-scale models.
Support development of efficient and scalable components across areas such as training platforms, inference systems, compilers, and distributed systems.
Implement and optimize system modules, tooling, or frameworks.
Collaborate with researchers and engineers to support research and system development.
Minimum Qualifications
Currently pursuing a Bachelor's or Master's degree 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++.
Experience with systems programming, distributed systems, compilers, or performance optimization through coursework, research, or projects.
Preferred Qualifications
Experience with large-scale systems, parallel or distributed computing, or performance optimization. Familiarity with system design, debugging, and profiling tools.
Strong problem-solving ability and ability to work collaboratively in a technical environment.
Numbers & Facts
Location
Seattle, WA
Skills
Algorithmsunmatched
Artificial Intelligence (AI)unmatched
C Programming Languageunmatched
C++ Programming Languageunmatched
Computer Programmingunmatched
Computer Scienceunmatched
Data Structuresunmatched
Debugging Toolsunmatched
Distributed Computingunmatched
Large-Scale Systemsunmatched
Machine Toolunmatched
Mathematicsunmatched
Parallel Computingunmatched
Performance Tuning/Optimizationunmatched
Problem Solving Skillsunmatched
Python Programming/Scripting Languageunmatched
Reinforcement Learningunmatched
Research Skillsunmatched
Systems/Internals Programmingunmatched
Team Playerunmatched
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