The Role
Design and build development and production platforms for new products, work on generative AI features, collaborate with cross-functional teams, enhance engineering productivity, and ensure system reliability.
Summary Generated by Built In
You will work on building generative AI inference infra at an unprecedented scale. You’ll be responsible for Luma’s REST APIs, and backend systems. The ideal candidate is product-minded, has strong coding skills and experience building and deploying software at scale. You should enjoy working with a fast-paced team to build amazing products, while maintaining high engineering standards.
Responsibilities
- Design and build the development and production platforms that power our new products, enabling reliability and security at scale
- Own the development of new user-facing generative AI features and product experiences end-to-end.
- Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world.
- Accelerate engineering productivity by empowering your fellow engineers with excellent tooling and systems.
- Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed.
Experience
- 10+ years of engineering experience in various tech environments, including product-driven companies.
- Strong python skills and deep understanding of end to end backend systems, databases, authorization.
- Experience with JavaScript and React for front-end development, and proficiency in Python or any backend language, demonstrating adaptability and a willingness to learn across the stack.
- Has prior experience working in startup environments, either as a founder or an early-stage engineer.
- Has prior work experience working with user facing API’s.
- Please note this role is not meant for recent grads.
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Top Skills
JavaScript
Python
The Company
What We Do
Luma is a multimedia platform that delivers personalized movie and TV program selections from a range of sources to its viewers.