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.

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.)

Designer

You're a designer who can code or deeply understands developer tools. You'll help us build a design-led organization.

Machine learning is going to become a huge part of how software will be built, but all the tools and processes are still mostly undefined.

This job isn't just making a bunch of user interfaces for a developer tool. You'll design what a machine learning model is, how models should be deployed, how the workflows should work, how teams should collaborate on models, and so on. All this stuff hasn't been figured out yet.

We're looking for the right person, not just someone who checks boxes, so you don't need to satisfy all of these things. But, you might have some of these qualities:

Infrastructure engineer

You're an infrastructure engineer who has experience building and operating things at scale.

We're building the fastest way to deploy machine learning models. When somebody pushes a model to Replicate, we optimize it, pick the right GPU, deploy it on a cluster, automatically scale it from zero to n, and so on. All the hard stuff that companies doing ML struggle with.

Instead of being an infrastructure engineer at one of those companies, you could work for us and force-multiply yourself across thousands of companies.

We're looking for the right person, not just someone who checks boxes, so you don't need to satisfy all of these things. But, you might have some of these qualities:

Email us: jobs@replicate.com

ML engineer

You're an ML engineer who is an expert at productionizing and optimizing machine learning models.

We have a huge library of community-contributed machine learning models. We're going to maintain some of the most popular ones so they're fast and reliable. You'll own this model library.

It'll involve implementing open-source models, optimizing them, and doing general maintenance on them. It's part ML engineer, part open-source gardener.

We're looking for the right person, not just someone who checks boxes, so you don't need to satisfy all of these things. But, you might have some of these qualities:

Email us: jobs@replicate.com

Model builder

We want to make every machine learning model runnable with a single line of code. Problem is, most models are just scraps of code on GitHub. Or, they're missing their model weights or locked up inside Colab notebooks.

We want to find all the best open-source machine learning models and get them working. We open pull requests to fix up their GitHub repositories and make Replicate pages for them. For people who are trying to push models to Replicate themselves, we help and support them on Discord.

You'll help us make machine learning reproducible. It's fun, flexible work. It could be full-time or part-time. You might be a PhD student or ML hacker looking for something on the side. You'll do a ton of open-source work.

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

Email us: jobs@replicate.com

Product engineer

You're a generalist engineer, leaning towards frontend/product. You've probably worked on developer tools or APIs before, and have a refined sense of what makes an excellent developer tool.

We have this website (currently React + Django), an open source CLI (Go + Python), and an API (Go + Kubernetes). The website and the CLI is probably where you'll be spending most of your time, but you might be touching any part of the stack, as well as all the other things that happen in the early stage of a company (talking to users, doing support, etc).

We don't mind what particular skills you already have. We figure you can pick up something new quickly.

We're looking for the right person, not just someone who checks boxes, so you don't need to satisfy all of these things. But, you might have some of these qualities:

Email us: jobs@replicate.com

Replicate