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Software Engineering Intern
Location
California
Posted
158 days ago
Salary
$35 - $40 / hour
Seniority
Entry Level
Job Description
Software Engineering Intern
Evident Scientific
This position is open for both Remote (US) and in-person (San Francisco, CA). About Olive We’re building the fastest way for companies to create internal tools—just by describing what they need in natural language. From sales dashboards to trust & safety workflows, internal tools are the operational backbone at modern companies. But building them is still slow, repetitive, and a drain on engineering time. We’re changing that. Olive takes a prompt and creates full-stack, functional internal tools connected to company data in minutes. Our platform leverages LLMs and code generation to create rich, production-grade tools that unlock new levels of insight and execution. We’ve raised a $2.1M seed round from incredible investors and angels and are now scaling our team. This is an opportunity to build something difficult but game-changing, with speed and immense focus. If that excites you, please apply. The Role We’re looking for a high-impact engineering intern to join us this summer (or fall/spring). You’ll work directly with the founders, contribute across the stack, and push the limits of robust full-stack software creation with AI. This is a paid internship. You’ll contribute a ton and build on top of LLMs and agentic workflows to handle code generation, deployment, tool usage, and more for enterprise use cases. At the end of the internship, you’ll have built significant features and functionality that will make a huge impact. We’re a fun team, work hard and support each other, and think about the customer every step of the way to create delightful product experiences. You’re a great fit if you’re… Super technical (e.g. impressive personal projects, products, internship experience, etc.) Comfortable navigating ambiguity and owning product decisions Quick learner even when you don’t know something! (Nice to have) Experience with code generation, ML/AI, agentic workflows
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