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
Design and build scalable infrastructure for large-scale model training, evaluation, and inference.
Optimize distributed training systems across compute, memory, and communication.
Improve system reliability, efficiency, and observability for large-scale workloads.
Develop frameworks for evaluation, data processing, and model lifecycle management.
Co-design systems and algorithms to improve performance of foundation models.Minimum Qualifications:
Individuals who are completing or have recently completed a Bachelor's degree in Computer Science, Electrical Engineering, Electrical and Computer Engineering, Physics, Mathematics, or a related discipline.
Excellent coding ability, data structures, and fundamental algorithm skills, proficient in C/C++ or Python, etc.
Demonstrated interest or project experience in relevant areas.
Preferred Qualifications:
Experience in distributed systems, machine learning systems, or related areas through internships is preferred.
Strong problem-solving and collaboration skills.
Numbers & Facts
Location
Seattle, WA
Skills
Algorithmsunmatched
Artificial Intelligence (AI)unmatched
C Programming Languageunmatched
C++ Programming Languageunmatched
Computer Engineeringunmatched
Computer Scienceunmatched
Data Modelingunmatched
Data Processingunmatched
Data Structuresunmatched
Distributed Computingunmatched
Electrical Engineeringunmatched
Machine Learningunmatched
Mathematicsunmatched
Memory Hardwareunmatched
Performance Managementunmatched
Performance Modelingunmatched
Physicsunmatched
Problem Solving Skillsunmatched
Python Programming/Scripting Languageunmatched
Reinforcement Learningunmatched
Reliability Engineeringunmatched
Scalable System Developmentunmatched
Scientific Researchunmatched
Systems Reliabilityunmatched
Team Playerunmatched
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