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ReplitReplit

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Paid internship for quantitative students contributing to AI-powered software creation, systems optimization, and developer tooling. Candidates should demonstrate strong mathematical ability, curiosity about AI, and autonomous cross-functional collaboration.

About the job

Responsibilities

  • Contribute to engineering problems involving AI-powered software creation.
  • Collaborate with engineers, designers, and product managers on platform infrastructure.
  • Prototype novel approaches in AI, systems, or tooling using mathematical rigor.
  • Ship work that impacts developers globally.

Requirements

  • Currently pursuing a bachelor's, master's, or PhD in Mathematics, Computer Science, Computer Engineering, Statistics, Physics, or a related quantitative field.
  • At least one semester of school remaining after the internship.
  • Demonstrated excellence in competitive mathematics, quantitative research, or advanced coursework.
  • Curiosity about AI, agent systems, company building, or developer tooling.
  • Strong first-principles thinking and mathematical intuition.
  • Ability to work autonomously and collaborate cross-functionally.
  • Strong communication skills for explaining quantitative concepts to technical and non-technical audiences.
  • Curiosity, speed, and willingness to iterate quickly.

Nice-to-haves

  • Experience with competitive mathematics such as IMO or IOI.
  • Projects built on the Replit platform.

Benefits

  • Competitive salary and equity.
  • 401(k) program with a 4% match for US employees.
  • Health, dental, vision, and life insurance.
  • Short- and long-term disability coverage.
  • Paid parental, medical, and caregiver leave.
  • Flexible time off and holidays.
  • Commuter benefits for in-office US employees.
  • Monthly wellness stipend.
  • Autonomous work environment.
  • In-office setup reimbursement.
  • Quarterly team gatherings.
  • In-office amenities.

Skills

Artificial Intelligence, Machine Learning, Mathematics, Optimization, Systems Engineering, Quantitative Research, Python, Developer Tooling

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