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 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 San Francisco, CA (specifically The Mission) 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.)

You’re a generalist data and analytics expert who thrives on developing data infrastructure at scale. You act like an owner and feel a desire to lead; you’ve likely been a data engineer at traditional companies but you’re ready to amplify your impact as the first data hire at a leading AI startup.

Replicate is building the fastest way to deploy machine learning models. We offer access to all types of open source models across modalities and levels of customization. The business is complex and we need a solid data foundation to guide decisions and hold ourselves accountable. You’ll be responsible for owning this foundation across the company.

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 probably have some of these qualities:

• Think like a software engineer: You put things in GitHub, use continuous integration, give things good names, make it consistent with how we do things in the product. We want to create data systems that integrate with the rest of our systems, not their own silo with a different culture.
• Experience building 0→1: You’ve set up data stacks and pipelines from scratch in the past.
• Expert with SQL and other common analytics tools: You know your way around BI tools like Metabase and can leverage them to deliver actionable insights.
• Agility and efficiency: You can move fast and prioritize effectively, delivering 80/20 solutions that address core needs.
• Experience with usage-based businesses: You understand the nuances of analyzing usage-based businesses from the ground up.
• Collaboration and partnership: You can work collaboratively with Finance, Product, Infrastructure, and Growth teams to create and maintain dashboards that measure key business metrics. You’re a solid communicator and can help teams pull together a story; you go beyond reporting metrics, diving deeper to understand what’s driving the numbers.

This role is based in our San Francisco office.

We have a web product (currently React + Django), an open source CLI (Go + Python), and Kubernetes ML serving infrastructure.