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Research Engineer (Agentic systems, AI, Full-Stack)
Physical Superintelligence
San Jose, USA
Full-time
Mid
Hybrid
Discovered 1 weeks ago
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Role Overview
Physical Superintelligence is a stealth startup with roots at Google, Harvard, Meta, MIT, Oxford, Johns Hopkins, Cambridge, and the Perimeter Institute building AI systems to discover new physics at scale. We are seeking engineers to build platform infrastructure at the intersection of computational science, AI systems, and software engineering.
Our mission is to discover and commercialize transformative physics breakthroughs at scale with artificial superintelligence - safely, verifiably, and for broad public benefit.
The last century's golden age of physics gave us transistors, lasers, and nuclear energy. We believe artificial superintelligence will unlock the next one. We're creating the infrastructure to industrialize scientific discovery and usher in this new era.
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PythonReactTypeScriptNext.jsPostgreSQLRedis
Full Job Posting
Overview
Physical Superintelligence is a stealth startup with roots at Google, Harvard, Meta, MIT, Oxford, Johns Hopkins, Cambridge, and the Perimeter Institute building AI systems to discover new physics at scale. We are seeking engineers to build platform infrastructure at the intersection of computational science, AI systems, and software engineering.
Our mission is to discover and commercialize transformative physics breakthroughs at scale with artificial superintelligence - safely, verifiably, and for broad public benefit.
The last century's golden age of physics gave us transistors, lasers, and nuclear energy. We believe artificial superintelligence will unlock the next one. We're creating the infrastructure to industrialize scientific discovery and usher in this new era.
Role and Responsibilities
- Develop a complex agentic system to support emerging superintelligence, with a focus on solving challenges in physics.
- Work across computational science simulation, AI systems, full-stack development, and infrastructure to build the platform enabling AI-driven physics discovery. This role requires fluency in scientific computing concepts, modern software engineering practices, machine learning infrastructure, and production systems design.
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