Startups · AI

Backend Engineer - Infrastructure

Heygen · Los Angeles, San Francisco, Palo Alto, Toronto · On-site

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About Heygen

Create AI videos from your ideas using HeyGen. Input text, image, or audio to create complete videos with narration, captions, visuals, and animations. Backed by Conviction.

About the role

As a Backend Engineer (Infrastructure) at HeyGen, you'll spearhead the development of core systems and infrastructure crucial to powering our products. Your expertise will be instrumental in crafting scalable, reliable, and efficient backend systems tailored to accommodate our expanding user base.

What they're looking for

  • Bachelor's degree in Computer Science, Engineering, or a related field
  • 2+ years of experience working on scalable and performant systems
  • Proficiency in python or c++
  • Experience with relational and NoSQL databases, such as PostgreSQL, MySQL, MongoDB
  • Familiarity with cloud platforms like AWS, Azure, or GCP
  • Strong knowledge of API design and development
More about this role

At HeyGen, our mission is to make visual storytelling accessible to all. Over the last decade, visual content has become the preferred method of information creation, consumption, and retention. But the ability to create such content, in particular videos, continues to be costly and challenging to scale. Our ambition is to build technology that equips more people with the power to reach, captivate, and inspire audiences.

Learn more at www.heygen.com . Visit our Mission and Culture doc here .

As a Backend Engineer (Infrastructure) at HeyGen, you'll spearhead the development of core systems and infrastructure crucial to powering our products. Your expertise will be instrumental in crafting scalable, reliable, and efficient backend systems tailored to accommodate our expanding user base.

  • System Development: Design, develop, and deploy scalable and efficient foundational systems. Examples include:
  • Data Infrastructure: Forge the next generation of data systems to fuel our analytics
  • Cloud Infrastructure: Multi-vendor GPU capacity management and scheduling
  • ML Infrastructure: Construct the ML training infrastructure to enhance our AI researchers’ productivity, and inference...

Read the full posting on Heygen's site ↗

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