We’re making machine learning easier and safer to use.

Machine learning can now do some extraordinary things: it can understand the world, drive cars, write code, make art.

But, it's still extremely hard to use. Research is typically published as a PDF, with scraps of code on GitHub and weights on Google Drive (if you’re lucky!). Unless you're an expert, it's impossible to take that work and apply it to a real-world problem.

We’re making machine learning accessible to everyone. People creating machine learning models should be able to share them in a way that other people can use, and people who want to use machine learning should be able to do so without getting a PhD.

With great power also comes great responsibility. We believe that with better tools and safeguards, we'll make this powerful technology safer and easier to understand.

Who we are

Andreas Jansson
Andreas Jansson

Built research tools & infrastructure at Spotify. PhD in ML for music.

Ben Firshman
Ben Firshman

Product at Docker, creator of Docker Compose.

Chenxi Whitehouse

PhD candidate in visual language understanding.

Dashiell Stander

Machine learning dilettante.

Dominic Baggott

Engineering at GOV.UK, NHS.UK. Leadership at a civic tech agency.

Jillian Ross
Jillian Ross

PhD student in deep learning at MIT CSAIL.

Zeke Sikelianos
Zeke Sikelianos

Engineering at GitHub, npm, Heroku. Creator of Swagger.

Join us

We're looking for a few people to join our small team.

We're a kind, creative, hard-working bunch. We care about our work and our users. We're humble and show humility. We're looking for the same in the people we work with.

When starting this company, we thought: instead of getting a job at the best place to work, let's make that best place to work. We want to work with the best people in an inclusive, supportive environment. And, just have fun while we're at it. You will help us make that place.

You can be located anywhere. We have a beautiful office in Berkeley, CA where some of us work, but we operate as a remote-first company across American and European timezones.

We want our team to feel invested in what we're building. We pay market salary, but well-above market equity. And, all the usual things. (We're European so you'll get really good healthcare.)

Community & advocate

We are looking for people with ML skills who love teaching, getting people excited about things, and working with communities. You might be a researcher looking for a more people-facing role, an ML evangelist working at a company, or a PhD student looking for some work on the side.

You will help us make every ML researcher know of and love Replicate. That might involve building fun projects with Replicate and writing about them. It might be organizing meetups, making videos, writing tutorials. You've probably got better ideas than we do.

We also have an existing community of researchers on Replicate, Discord, GitHub, and Twitter. You will help us support and grow that community.

We're looking for the right person and are not just checking boxes. But, you might have some of these qualities:

This role could be full-time or part-time. It might be multiple people, depending on what your skills are.

Email us: jobs@replicate.com

Replicate