We're an applied research lab working towards a future where engineers can use natural language to do CAD tasks end-to-end. With high-level commands like "Hey Camfer, design a gearbox w/ a 3:1 ratio for this motor!", our agents will autonomously design the system, source off-the-shelf parts, and create drawings to be sent off for manufacturing (like Jarvis for Ironman). Last fall, we won both Y Combinator's internal demo day and OpenAI's o1 hackathon! Here's a clip of Sam Altman talking about Camfer.

Our first step is creating a tool that allows engineers to use text, images, and mechanical drawings to generate feature-rich CAD models directly in SolidWorks and Onshape. We've got a few pilot users at companies like Physical Intelligence using our v0.

We're a small, young team of software devs and researchers who have a love for CAD and design. Our founders are FRC world champions, UC Berkeley alumni / researchers, ex-AWS, and ex-Meta.

We finished YC in October and raised a $4.8M seed round. Our investors include Y Combinator, Next47, Bloomberg Beta, Octave Fund, and the founders of Dropbox, Airtable and Clari.

We're in-person in SF. We have an espresso machine, meals provided every day, a fully stocked fridge, and lots of natural light!

Working at Camfer

At Camfer, interns are given the same autonomy as full-time engineers and researchers. Native Sparse Attention was an intern project! The only bottlenecks on your impact will be your imagination, taste, and agency. We are also very young (average age is ~23).

We’re building a flat and talent dense organization. We enjoy deep, multi-disciplinary thinking, high-conviction bets, and having fun!

Role

We are looking for people who:

• Are generalists that have worked with a broad range of programming languages and systems
• Are passionate, creative, curious, and truth-seeking
• Have the ability to adapt quickly and are always learning

Everyone is full-stack: look at data, write training code, build evals, do product work, etc.

Some example projects you might work on:

• Building gyms and training models with RL for specific CAD skills
• Developing new AI-native UI components for the future of CAD
• Generating datasets for multi-modal understanding (e.g. ingesting pointclouds)
• Training draft models for speculative decoding
• Optimizing model hosting/inference for more robust generations

Note: this listing is for summer, but if you want to come in the spring that is also fine