San Francisco
2 years ago

Job Overview

Job Type
FullTime
Pay
$100K – $550K

Job description

Salary:
USD 100,000 - 550,000 per year
Location:
San Francisco, United States
Work arrangement:
On-site

Role Summary

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.

If you feel you have something to contribute to the mission and you're a high-energy person, we would love to explore working together in roles that might not be listed on our careers page. We make exceptions for exceptional people.

COMPENSATION, BENEFITS AND PERKS (US)

  • Annual salary range: $100K - $550K
  • Equity is a significant part of total compensation, in addition to salary
  • 401(k) plan with 6% salary matching
  • Generous health, dental and vision insurance for you and your dependents
  • Unlimited paid time off
  • Option to work in-person in SF or remotely
  • Visa sponsorship and relocation stipend to bring you to SF, if possible
  • A small, fast-paced, highly focused team

Salary: $100K – $550K

About the Company

  • Integrity. Words and actions should be aligned
  • Hands-on. At Magic, everyone is building
  • Teamwork. We move as one team, not N individuals
  • Focus. Safely deploy AGI. Everything else is noise
  • Quality. Magic should feel like magic

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.

Role:
<insert-job-you-excel-at/>
Job Type:
FullTime

Company profile

magic.dev

magic.dev

Magic (magic.dev) is an AI company working toward building safe AGI to accelerate humanity's progress on the world's most important problems. It builds frontier code models to automate software engineering and research, holding that automating AI research and code generation is the most promising path to safe AGI and to solving alignment reliably. Magic's approach combines frontier-scale pre-training, domain-specific reinforcement learning, ultra-long context and inference-time compute.

Total Raised
$768M
Key Investors
Nat Friedman, Daniel Gross, CapitalG, Elad Gil, Sequoia

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