Why this role stands out
This paid fellowship at Menlo offers a unique opportunity to dive into cutting-edge AI development with direct mentorship and ownership of impactful projects, ideal for driven mid-senior professionals seeking accelerated growth and hands-on experience. You'll thrive in this hybrid role if you're eager to contribute significantly to open-source and production AI systems, and you're encouraged to apply to explore this exciting path.
Quick overview
Job description
The Role
Menlo builds open source and production AI systems, from the brain, to developer facing tools to the runtime infrastructure and humanoid platform underneath. This fellowship is deliberately open ended: tell us your strengths and we'll match you to high impact work across software engineering, systems, applied AI, or research. You'll be hands on from day one, with a Menlo engineer or researcher directly responsible for your mentorship and your results. You own deliverables at the same level as the team you join. We expect you to contribute, not observe.
This is a paid internship program that runs year round. Candidates go through a rigorous interview process and get matched with a senior researcher or engineer working on real world problems.
What You'll Do
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.
Logistics
3 months minimum, based in one of our offices: San Francisco, Ho Chi Minh City, or Singapore
Paid role.
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.
Why Join Menlo
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.
A Note on AI
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
We hire talented people from a wide range of backgrounds. If you're excited about a role but don't meet every bullet, we still encourage you to apply. Menlo Research is an equal opportunity employer and does not discriminate on the basis of any legally protected characteristic. Menlo provides reasonable accommodations during the application process. If you need one, please let your recruiter know.
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