Magic is working on frontier-scale code models to build a coworker, not just a copilot. Come join us: http://magic.dev
Magic is working on frontier-scale code models to build a coworker, not just a copilot. Come join us: http://magic.dev
Headquarters: San Francisco, CA
Focus: Frontier-scale generative AI models for code and research automation
Founding year: 2022
Founders: Eric Steinberger; Sebastian De Ro
Total funding (reported): Approximately $465M–$515M
Employee count (snapshot): 99
Automating software engineering and AI research using frontier-scale language models.
2022
Artificial intelligence; developer tools
$320,000,000
Reported contributions from Eric Schmidt, CapitalG (Alphabet), Sequoia, Atlassian, Jane Street, and individual investors including Nat Friedman, Daniel Gross and Elad Gil.
$23,000,000
Participation from Elad Gil, Nat Friedman and Amplify Partners.
“Includes strategic and high-profile investors (Eric Schmidt, CapitalG/Alphabet, Sequoia, Atlassian, Jane Street) and notable individual investors (Nat Friedman, Daniel Gross, Elad Gil).”
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Magic’s mission is to build safe AGI that accelerates humanity’s progress on the world’s most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal.
About the role: As a Software Engineer on the Product team, you’ll be responsible for building and maintaining our product surfaces, which are vertically integrated into our model (LTM) and infrastructure. These surfaces are used both by our end-users (customers) and our technical staff internally. Engineers on the product team are comfortable working across the technical stack, from building user interfaces to working on backend API services, and everything in between. Product engineers collaborate directly with our design team, as well as product leadership, and our machine learning engineering teams.
What we’re looking for:
Magic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience.
Our culture:
Compensation, benefits, and perks (US):