Why This Role Stands Out
This paid hybrid internship at Replit offers an exceptional opportunity to tackle complex challenges at the intersection of AI and software development, directly impacting millions of users worldwide. You'll thrive here if you possess strong quantitative and creative skills, eager to collaborate with top executives and engineers on cutting-edge projects while gaining invaluable experience in a dynamic, growth-oriented environment. Apply now to shape the future of AI-native software creation!
Quick Overview
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:
Contribute to real engineering problems that push the boundaries of AI-powered software creation
Collaborate with engineers, designers, and product managers on infrastructure that powers Replit's platform
Prototype novel approaches to problems in AI, systems, or tooling where mathematical rigor is the differentiator
Ship work that impacts millions of developers globally, in an environment where your ideas are heard and often implemented
Required Skills and Experience:
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 schooling remaining after the internship
Demonstrated excellence in competitive mathematics such as IMO and IOI, quantitative research, or advanced coursework
Genuine curiosity about AI, agent systems, company building, or developer tooling
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:
First-principles thinking: Ability to break down complex problems from the ground up and reason about them rigorously
Mathematical intuition: Strong grasp of the underlying math behind machine learning, optimization, or systems
Self-directed and autonomous: Capable of working independently while collaborating well with cross-functional teams
Strong communication: Ability to explain complex quantitative concepts to both technical and non-technical audiences
Curiosity and speed: Genuine excitement for hard problems and the drive to iterate quickly
Full-Time Employee Benefits Include:
π° Competitive Salary & Equity
πΉ 401(k) Program with a 4% match (US Only)
βοΈ Health, Dental, Vision and Life Insurance
π©Ό Short Term and Long Term Disability
πΌ Paid Parental, Medical, Caregiver Leave
π Flexible Time Off (FTO) + Holidays
π Commuter Benefits (In-Office & US Only)
π± Monthly Wellness Stipend
π§βπ» Autonomous Work Environment
π₯ In Office Set-Up Reimbursement (In-Office Only)
π Quarterly Team Gatherings
β In Office Amenities (In-Office Only)
Want to learn more about what we are up to?
Interviewing + Culture 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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