Software Engineer, Quantum Compiling

Google is seeking a Software Engineer to join their Quantum Computing team, focusing on quantum compiling and error correction. This role is critical to Google's mission of building a large-scale quantum computer capable of complex, error-corrected computations. The position involves developing software for compiling logical quantum algorithms to low-level instructions that can operate fault-tolerantly in the presence of noise and device imperfections.

The role requires strong programming skills in C++ and Python, with the engineer working on developing compiler software that translates high-level quantum algorithms into low-level quantum operations. You'll collaborate closely with research scientists on design discussions and pair programming, while also working on software development under evolving requirements. The position involves integration with qubit control systems and implementing robust software engineering practices.

This is an exciting opportunity to work at the cutting edge of quantum computing technology at one of the world's leading tech companies. The role offers competitive compensation ($141,000-$202,000 base salary) plus bonus, equity, and comprehensive benefits. You'll be part of Google Quantum AI's mission to unlock the full potential of quantum computing and enable meaningful applications that could revolutionize various fields.

The ideal candidate will have at least 2 years of software development experience and a strong background in computer science or a related field. While quantum computing knowledge is valuable, the role emphasizes strong software engineering skills and the ability to collaborate effectively with researchers and other technical teams. The position offers the opportunity to work in either Los Angeles or Goleta, CA, contributing to groundbreaking advances in quantum computing technology.

Working at Google, you'll be part of a company culture that values diversity, innovation, and technical excellence. The role provides opportunities for growth and learning while working on cutting-edge technology that could fundamentally change how we solve complex computational problems.