menlo - Fellows
Responsibilities
• Own a real project end to end, from problem definition through implementation, testing, and documentation. • Ship production grade work in one or more areas: product engineering, systems, infrastructure, applied AI, or research. • Work on core Menlo projects, including developer tooling, model runtime and performance, automation, and reliability improvements. • 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 for the team to adopt. • Collaborate closely with engineers and researchers through code reviews and technical discussions. • What We Look For • University, high school or mid-career individuals looking for a crash course in physical AI and robotics • The ability to read unfamiliar codebases and make safe, well scoped changes. • Practical debugging skills: you can isolate problems and validate fixes. • A grasp of software or hardware engineering basics: testing, version control, and review. • A high ownership mindset and the ability to work independently with fast feedback loops. • Above all, we hire for slope: how fast you grow matters more than where you start. • 3 months minimum, based in one of our offices: San Francisco, Ho Chi Minh City, or Singapore • Open to pre university and university students. • You'll need existing work authorization for your office location, as we don't provide visa sponsorship for this role.
Benefits
• You'll do real work that ships, not busywork on the bench. Genuine ownership, direct mentorship from the people building Asimov, and a chance to prove yourself on hard problems alongside some of the most curious and driven people you'll meet. If you want your work to matter beyond a paper or a demo, this is the place. • You don't need deep AI expertise for every role, but we do expect everyone at Menlo to be intellectually curious, drawn to tinkering and discovery, and excited to use AI as a real collaborator in their work. For some roles, AI fluency is a core requirement. When that's the case, we'll say so explicitly in the qualifications. People who thrive here don't treat AI as a novelty. They use it to think better, and make their work easier for others to build on. • Equal Opportunity and Accommodations
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