
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
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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).”
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.
Software Engineer – Data Tooling Role Overview We're looking for someone to lead developer experience and data tooling for our pre-training data team. This person will build internal tools and infrastructure that make the team more productive—dashboards, CLIs, data exploration UIs, and the systems that tie them together.
The role is focused on DX and tooling—we're looking for someone who genuinely loves hacking on things, shipping fast, and tinkering.
What You'll Do
What We're Looking For Nice-to-Haves
Ideal Background (in rough priority order)
Not Required
Why This Role You'll have significant ownership over how a high-performing team works day-to-day. The scope is broad, the feedback loops are fast, and the work directly impacts how quickly we can move on core research and data efforts.
Our culture:
Compensation, benefits, and perks (US):
Compensation Range: $240K - $370K