Replicate
Run machine learning models in the cloud
Creative AI Engineer
About the role
Replicate lets you run machine learning models in the cloud. We’re not just another AI company; we’re a team of developers, engineers, and innovators from organizations like Docker, Spotify, Dropbox, GitHub, Heroku, NVIDIA, and more. We’ve built foundational technologies like Docker Compose and OpenAPI, and now, we’re applying that expertise to make AI deployment as intuitive and reliable as web deployment.
The Models team at Replicate keeps our public model library up to date with all the latest generative AI models. We make sure all the popular models are fast, reliable, and easy to use. We use and test models to find each model's unique features. We have our ear to the ground and build new models and pipelines that our users and the community want by opening up the black boxes of open-source models.
As a Creative AI Engineer on the Models team, you'll be hacking on image/video/audio models at the bleeding edge, sometimes before they're publicly released. You'll spend time with the models and really learn their strengths and weaknesses. You'll build in public and share your findings with the community. You'll sometimes create new open-source models and tools in Python and ComfyUI.
About you
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You’re an active part of the gen AI community — you spend an inordinate amount of time on X, Discord, Reddit, etc., keeping up with all the latest models and sharing your work.
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You can code. You write clean, idiomatic Python and know how to work with machine learning code.
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You’re comfortable with ComfyUI.
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You do creative, interesting things with generative AI, focused on image and video generation.
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You’re a great communicator, both online and in person.
What you’ll be doing
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Exploring new image/video/audio models (sometimes before they’re available to the public). You’ll find the edges of those models, discover what they’re good at, interesting use cases, etc.
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Publicly building and teaching people how to do interesting things with new models.
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Open up the black boxes of open-source models and add new interesting features for the community and our customers.
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Building pipelines of models in code and/or ComfyUI.
These aren’t hard requirements, but we definitely want to talk with you if…
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You understand machine learning, can reason about model architecture, and understand math.
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You’re an artist.
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You’re a designer.
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You have experience across image, video, as well as speech, audio, and music models.
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You can build modern web apps around models.
This role can be remote (anywhere in the United States, UK, or the EU) or in-person. If you're local to the Bay Area, we would like you to work out of our San Francisco office at least 3 days a week.
About the interview
Answer these questions to be considered for this job:
What do you wish you could do with AI that you can’t do at the moment?
What’s the thing you’re most proud of that you’ve done with AI?
What’s your favorite but largely underrated AI model?
If you were asked to make a greeting card AI model with accurate text and print resolution, what approach would you take?
About Replicate
What we're doing
Machine learning can now do some extraordinary things: it can understand the world, drive cars, write code, make art.
But, it is 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!). It is near-impossible to take that work and apply it to a real-world problem, unless you are an expert.
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 it without getting a PhD.
With great power also comes great responsibility. We believe that with better tools and safeguards, we will make this powerful technology safer and easier to understand.
How we work
We're a bunch of hackers, engineers, researchers, and artists.
We obsess about the details of API design and the right words for things. We're defining how AI works so we'd better get it right.
We make fast and reliable infrastructure. That's what a good infrastructure product is. We're not afraid to build things from scratch to make it the fastest.
We use AI for work. We use AI for play. We find unexplored parts of the map and create new techniques ourselves. We open-source it all.
We build in public, for the community. We want AI to work like open-source software so everyone benefits from it.
We're led by engineers. We all write code. (Or, we get ChatGPT to help.) There aren’t any meetings about meetings.
We've worked at places like Docker, Dropbox, GitHub, Heroku, NVIDIA, Scale AI, and Spotify. We've created technologies like Docker Compose and OpenAPI.
We're here to build a big company. We're ambitious and hard-working. We're not here to just build nice things.
