Machine Learning Cloud Infrastructure Engineer
UniversalAGI
About this role
A Machine Learning Cloud Infrastructure Engineer at UniversalAGI is responsible for building and scaling the infrastructure that supports AI for physics, focusing on training and serving foundation models in production. This role involves designing low-latency model serving systems, optimizing distributed training across multi-GPU clusters, and integrating customer-specific solutions while ensuring compliance with enterprise security requirements. The engineer will work directly with the CEO and founding team to enhance infrastructure capabilities and address customer needs effectively.
Skills
About UniversalAGI
www.universalagi.comUniversalAGI is revolutionizing physical systems engineering by automating the entire product lifecycle using artificial intelligence. The company is focused on developing foundation models for physics that facilitate end-to-end automation, from initial design through to optimization, validation, and production. By leveraging these advanced AI models, UniversalAGI enables engineers to iterate rapidly, explore a vast array of design variants, and uncover innovative solutions that traditional methods may overlook. Through their cutting-edge technology, UniversalAGI aims to accelerate human progress and innovation in various transformative sectors.
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About UniversalAGI
Headquarters
San Francisco, CA
Company Size
201-500 employees
Founded
2018
Industry
Technology
Glassdoor Rating
4.2 / 5
Leadership Team
Sarah Johnson
Chief Executive Officer
Michael Chen
Chief Technology Officer
Emily Williams
VP of Engineering
David Rodriguez
VP of Product
Jessica Thompson
Chief Financial Officer
Andrew Park
VP of Sales
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and employee contacts for UniversalAGI.
Salary
$180k – $242k
per year