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Software Engineer

slai

slai

Software Engineering
Cambridge, MA, USA
Posted on Friday, May 5, 2023
$100K - $180K / 0.20% - 0.75%
Location
Cambridge, MA
Job Type
Full-time
Experience
Any (new grads ok)
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Eli Mernit
Founder

About the role

Beam is a tool to quickly build machine learning-powered applications. Our platform helps developers run their code on serverless GPUs, deploy highly performant APIs, and rapidly prototype ML models — without managing any infrastructure.

We’re looking for another engineer to join our team. Our backend APIs are Python, our infra code is Golang, and the frontend is React / TS. This is a fully-remote, international role – we’re native to tools like Slack, Zoom, and Google Docs, and this works pretty well for us. We try to keep distractions to a minimum, we have hackathons at our office, and we value getting into a flow state at work.

Skills & Experience

  • Experience building large features from conception to launch
  • Comfortable with Python or Golang (you'll write both here), and familiarity with Kubernetes
  • Able to setup cloud resources -- you know your way around the cloud console and can make sense of Terraform
  • Enthusiasm for developer tools, cloud native technologies, and machine learning

Benefits

  • Competitive salary and meaningful equity
  • Flexible work environment – work remotely, or from our HQ in Cambridge, MA
  • Health, dental, and vision benefits with 90% coverage for you and 50% for dependents
  • Laptop & home-office equipment stipend
  • Fitness stipend, learning budget, and much, much more

About Beam

Beam is a tool to quickly build machine learning-powered applications. Our platform helps developers run their code on serverless GPUs, deploy highly performant APIs, and rapidly prototype ML models — without managing any infrastructure.

Machine learning is eating software, but it’s still difficult for developers to leverage ML in their products. Today, companies are spending months building their own ML platforms, or relying on outdated tools that were originally designed for academics.

We believe that for ML to reach widespread adoption, the underlying infrastructure needs to be hidden from the user. We're building the fastest way for developers to go from an ML prototype to a production service.