Software Engineer - Research Infrastructure

Meta is seeking a Software Engineer to join their Research Infrastructure team, focusing on building cutting-edge systems that support crucial research projects. This role sits at the intersection of machine learning infrastructure and research support, where you'll work closely with researchers and engineers to develop solutions that scale the impact of Meta's research initiatives.

The position involves designing and implementing components that enable model deployment, data collection from research studies, and infrastructure scaling to support various research settings. You'll be responsible for creating efficient backend systems and reusable abstractions that help researchers work more effectively.

This is an excellent opportunity for someone with strong software development experience who wants to work on ML compute infrastructure and data pipelines. The ideal candidate should have experience with technologies like Docker, Kubernetes, PyTorch, and Python, and be comfortable working directly with researchers who may not have backend development expertise.

The role offers competitive compensation ranging from $56,250 to $173,000 annually, plus bonus, equity, and comprehensive benefits. You'll be working at Meta, a company at the forefront of social technology and immersive experiences, building technologies that help people connect, find communities, and grow businesses.

As part of Meta's Reality Labs division, you'll be contributing to the next evolution in social technology, moving beyond traditional 2D screens toward augmented and virtual reality experiences. This is a chance to shape the future of how people interact and connect in the digital space.

The position is available in either Redmond, WA or Burlingame, CA, offering the opportunity to work with world-class researchers and engineers in state-of-the-art facilities. Meta provides a collaborative environment where you can make a significant impact on the future of research infrastructure while working on challenging and meaningful problems.