Beam
AI Infrastructure for Developers
Software Engineer, Product
About the role
Beam helps developers build and run AI and LLM applications on serverless GPUs, without managing infrastructure. Hundreds of teams are using Beam to power their applications in production. And we have a thriving community of developers using our platform to build state-of-the-art apps with AI.
We’re looking to hire a Product Engineer to join the team. You’ll be responsible for building full-stack features, encompassing our Python SDK, React/Typescript app, and core backend APIs. You’ll own brand new features, communicating directly with customers to build things that make their lives easier.
Skills & Experience
- Full-stack experience with Python and React/Typescript (Golang is a nice-to-have)
- You’ve started a project from scratch, built an impressive side project, or been a founder
- Strong written and verbal communication skills. You’ll interact directly with customers, in addition to building new features.
- You are attentive to little details and value craftsmanship in your work
Benefits
- Competitive salary and meaningful equity
- Join a fast-growing pre-series A company at the ground floor
- Health, dental, and vision benefits with 90% coverage for you and 50% for dependents
- Opportunities to participate in events across the cloud native community
- 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 Today, companies are spending months building their own ML platforms, or relying on outdated tools that were originally designed for academics.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.
