Intern

About Transfyr

Transfyr is building physical AI for science.

Why is it that a professional athlete has dramatically more information about every play they make than a scientist has about the cause of any experimental failure? At Transfyr, we are building the infrastructure to make real-world scientific work legible, transferable, and reproducible.

Modern science is capable of extraordinary outcomes, but much of the most important insights never become explicit: how experiments are actually executed, protocols drift, how experts make gametime decisions on the fly, why experiments fail on Tuesdays. This tacit knowledge is rarely captured, making it difficult to reliably reproduce results, much less hand off protocols to new team members or collaborators. We believe our systematic failure to capture tacit knowledge is holding back the entire industry.

We’re building systems that operate directly in real laboratory environments to elucidate, capture, and interpret this missing information. Our platform records and analyzes multimodal data about how scientific work is performed and turns it into durable, operational knowledge. In doing so, we are also building the world’s largest commercial dataset on real-world scientific execution.

This foundation is critical not only for driving elite human performance today, but for enabling meaningful automation tomorrow. Physical AI systems cannot learn from outcomes alone; they require rich, grounded records of how work is actually done in the real world.

Want to learn more? You can read some of our writings here.

The Role

Interns at Transfyr are embedded members of the technical team. You will work on real systems alongside software engineers, AI/ML engineers, perception engineers, and scientists, contributing directly to products and infrastructure that run in live laboratory environments.

This is not a shadowing role or a collection of toy projects. Interns are expected to take ownership of scoped problems, make progress independently, and ship work that matters.

We are open to summer internships, term time internships, or flexible arrangements depending on availability and fit.

What you’ll accomplish with us

• Build Real Systems: Work on real technical problems across software, data, AI, or perception depending on your interests and strengths.

• Ship Work That Matters: Contribute code, experiments, or systems that are used by the team and evolve over time.

• Learn by Doing: Prototype quickly, test ideas against real data or real environments, and iterate based on failure.

• Grounded Collaboration: Work closely with engineers and scientists to understand how requirements emerge from reality rather than clean specs.

• Own Your Projects: Take ownership of defined projects and push them forward with guidance and feedback from the team.

• Grow on Frontier Systems: Learn how frontier technical systems are built, evaluated, and maintained in ambiguous, fast moving environments.

Who you are

• High Agency: Highly motivated and biased toward action. You take initiative and do not wait for perfect instructions.

• Comfortable in Ambiguity: Comfortable operating with incomplete context and learning what you need as you go.

• Deeply Curious: Curious about how real systems work and motivated to understand problems deeply.

• Fast Iteration: Able to take feedback, iterate quickly, and improve your work.

• Driven by Challenge: Excited by hard problems and willing to put in focused effort when it matters.

• Builder Mindset: Someone with a builder or founder mindset who wants responsibility, not just exposure.

What you know

• Technical Foundation: Currently pursuing or recently completed a degree in computer science, engineering, robotics, math, or a related technical field.

• Programming Fundamentals: Strong programming fundamentals.

• Systems Exposure: Some exposure to software systems, data pipelines, machine learning, computer vision, or robotics through coursework or projects.

• Learning Velocity: You do not need deep expertise in all of these areas. We care more about fundamentals, curiosity, and learning velocity.

Other things we like to see:

• A passion for and experience in science

• A passion for and experience with AI

• Demonstrated experience working in fast-moving/ambiguous environments (like startups!)

The basics:

• Interns receive market compensation with the opportunity to earn startup equity with a full time offer.

• Internships do not typically qualify for fringe benefits (e.g. health insurance), but exceptions may be made if the circumstances are appropriate