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.
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 an engineer who dreams in cycles and optimizations. You have a deep passion for squeezing every ounce of performance out of complex systems, whether that's rendering the latest AAA game title or optimizing large-scale distributed systems.
At Replicate, we're building the fastest way to deploy machine learning models. We're looking for someone who can bring their performance optimization expertise to the cutting edge of AI infrastructure.
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:
You might be particularly good for this job if:
While prior experience with AI or machine learning isn't required, you should be excited about applying your performance optimization skills to this domain. We believe your expertise in cycles, memory management, and systems-level thinking will translate well to the challenges of optimizing AI model inference and training.
We have a web product (currently React + Django), an open source CLI (Go + Python), and Kubernetes ML serving infrastructure.
fulltimeRemote (San Francisco, CA, US)Machine learning$150K - $250K3+ years
fulltimeSan Francisco, CA, USData science$150K - $200K3+ years
fulltimeRemote (San Francisco, CA, US)Machine learning$150K - $250K3+ years