Menlo Fellows (Internship)

About the Role
Menlo builds open source and production AI systems, including developer facing tools and runtime infrastructure. As an Engineering Intern, you will join a small team and ship real technical work across software engineering, systems, and applied AI, depending on your strengths. This role is deliberately broad so we can match you to high impact projects across the stack.
Key Responsibilities

• Ship production grade code in one or more areas, product engineering, systems, infrastructure, or applied AI.
• Work on core Menlo projects, including developer tooling, model runtime and performance, automation, and reliability improvements.
• Own small to medium scoped projects end to end, from problem definition to implementation, testing, and documentation.
• Debug real issues across codebases and environments, and propose fixes that improve correctness, performance, and maintainability.
• Write clear docs, runbooks, or internal notes that make your work easy to adopt by the team.
• Collaborate closely with engineers and researchers through code reviews and technical discussions

You Should Have

• Strong programming fundamentals and comfort building in at least one language, Python, C++, Rust, or Go.
• Ability to read unfamiliar codebases and make safe, well scoped changes.
• Practical debugging skills, you can isolate problems and validate fixes.
• Understanding of software engineering basics, testing, version control, and code review.
• High ownership mindset and ability to work independently with fast feedback loops

Nice to Have

• Experience with AI or ML stacks, PyTorch, inference runtimes, CUDA awareness, or performance profiling.
• Systems experience, Linux, networking basics, containers, Kubernetes, or distributed systems concepts.
• Contributions to open source projects or evidence of strong personal technical projects.
• Interest in developer experience, tooling, and making complex systems simpler to use