Software Engineer, Compiler, Scheduling and Optimization, Silicon

Google is seeking a Software Engineer to join their EdgeTPU compiler team, focusing on core optimization and scheduling algorithms for their next-generation compiler framework. This role is crucial in developing and implementing compiler technologies that power Google's AI and machine learning capabilities.

The position offers an opportunity to work at one of the world's leading technology companies, with a direct impact on how AI/ML workloads are optimized and executed on Google's custom silicon. You'll be working with cutting-edge technology, including Multi-Level Intermediate Representation (MLIR)-based compiler frameworks and the latest developments in Generative AI.

The role combines deep technical expertise in compiler optimization with practical applications in machine learning and hardware acceleration. You'll be collaborating with hardware architects, product managers, and researchers to shape the future of Google's AI infrastructure. This position is perfect for someone who has a strong background in compiler development and optimization, with an interest in machine learning and hardware/software co-design.

Key aspects of the role include developing parallelization and scheduling algorithms, optimizing compute and data movement costs, and working on efficient mapping of AI models to hardware instructions. You'll be at the forefront of implementing optimization algorithms and compiler transformation frameworks that directly impact the performance of Google's devices.

The compensation package is competitive, ranging from $141,000 to $202,000 base salary, plus bonus, equity, and comprehensive benefits. The position offers the opportunity to work from either Mountain View, CA or Bellevue, WA, putting you at the heart of Google's technical innovation centers.

This is an excellent opportunity for someone who wants to make a significant impact on the future of AI/ML computing while working with some of the best minds in the industry. The role offers both technical challenges and the satisfaction of seeing your work improve the performance of Google's AI systems used by billions of users worldwide.