ML infrastructure engineer at Replicate (W20)
$150K - $250K  •  
Run machine learning models in the cloud
San Francisco, CA, US / Remote
Full-time
3+ years
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 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.)

About the role

You're an infrastructure engineer, ideally with ML experience. We're growing fast and need your help scaling.

We serve machine learning models. We deal with GPUs, optimize models, write prediction servers, set up clusters, and so on. All the hard stuff that companies doing ML would rather not deal with.

Instead of being an ML infrastructure engineer at a single product company, 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 these things. But, you might have some of these qualities:

  • Experience building and scaling infrastructure at huge scale.
  • You can squeeze every last drop of performance out of a GPU.
  • You know your way out of CUDA error: device-side assert triggered.
  • Excellent communication skills. We think most of being a programmer is not programming. We want you to be able to communicate complex topics clearly, write down your thinking, write good docs, etc.
Technology

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

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