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Foster City, CAFull-timePosted 1mo agoStill listed 2 days ago
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Job overview
Replit is seeking a paid internship for quantitative and creative minds to work alongside top executives, engineers, designers, and finance teams on AI‑native software creation. Interns will tackle real engineering problems, collaborate on platform infrastructure, prototype novel AI approaches, and ship work impacting millions of developers worldwide.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation.
About the Role Join Replit's key teams across the company, such as AI Research, Strategic Finance, or the Office of the CEO, for a unique paid internship built for sharp quantitative and creative minds. You will work alongside our top executives, in addition to world-class engineers, designers, and finance team on some of the hardest problems in AI-native software creation and accelerating key areas of our business.
We are creating a dedicated track for students with strong mathematical backgrounds because the problems we are solving sit at the intersection of deep math and applied AI, including agent reasoning, systems optimization, and improving how our models learn and perform at scale. Your work will directly shape how millions of users build software.
You Will:
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Contribute to real engineering problems that push the boundaries of AI-powered software creation
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Collaborate with engineers, designers, and product managers on infrastructure that powers Replit's platform
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Prototype novel approaches to problems in AI, systems, or tooling where mathematical rigor is the differentiator
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Ship work that impacts millions of developers globally, in an environment where your ideas are heard and often implemented
Required Skills and Experience:
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Currently pursuing a Bachelor's, Master's, or PhD in Mathematics, Computer Science, Computer Engineering, Statistics, Physics, or a related quantitative field
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At least one semester of schooling remaining after the internship
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Demonstrated excellence in competitive mathematics such as IMO and IOI, quantitative research, or advanced coursework
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Genuine curiosity about AI, agent systems, company building, or developer tooling
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Extremely bullish on Replit and the future of AI-native software creation. We would love to see what you have built on the platform
What We Value:
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First-principles thinking: Ability to break down complex problems from the ground up and reason about them rigorously
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Mathematical intuition: Strong grasp of the underlying math behind machine learning, optimization, or systems
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Self-directed and autonomous: Capable of working independently while collaborating well with cross-functional teams
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Strong communication: Ability to explain complex quantitative concepts to both technical and non-technical audiences
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Curiosity and speed: Genuine excitement for hard problems and the drive to iterate quickly
Full-Time Employee Benefits Include: 💰 Competitive Salary & Equity 💹 401(k) Program with a 4% match (US Only) ⚕️ Health, Dental, Vision and Life Insurance 🩼 Short Term and Long Term Disability 🚼 Paid Parental, Medical, Caregiver Leave 🏝 Flexible Time Off (FTO) + Holidays 🚗 Commuter Benefits (In-Office & US Only) 📱 Monthly Wellness Stipend 🧑💻 Autonomous Work Environment 🖥 In Office Set-Up Reimbursement (In-Office Only) 🚀 Quarterly Team Gatherings ☕ In Office Amenities (In-Office Only)
Want to learn more about what we are up to?
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Self-driving Company
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Replit Agent at Scale
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AI Adoption
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Build Open-Source Apps
Interviewing + Culture at Replit
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Operating Principles
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Reasons not to work at Replit
To achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.
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