Staff Engineer, AI/ML Software Compiler

Position Overview

To provide the best candidate experience amidst our high application volumes, each candidate is limited to 10 applications across all open jobs within a 6‐month period.

Advancing the World's Technology Together – Our technology solutions power everyday tools and innovative products ranging from smartphones to hyperscale data centers. At the AGI (Artificial General Intelligence) Computing Lab, you will help tackle complex challenges posed by future AI/ML workloads by designing scalable platforms that balance performance and energy efficiency. Join us in revolutionizing the way AI/ML applications are deployed and executed to shape the future of computing!

Location: Daily onsite presence at our San Jose, CA office / U.S. headquarters in alignment with our Flexible Work policy.

Reports to: VP

Key Responsibilities

• Design and implement ML compilers for high-performance deep learning applications.
• Optimize compilers for efficient execution of deep learning models on various hardware platforms.
• Design a staged lowering infrastructure to meet rapidly evolving workload requirements effectively.
• Design an algorithm to optimize data locality to minimize energy consumption.
• Collaborate with hardware architects and developers to integrate new ML techniques and algorithms into the compiler.
• Work closely with cross-functional teams to define and deliver ML compiler features and improvements.
• Troubleshoot and debug compiler issues and provide technical support to customers.
• Contribute to developing ML compiler documentation and user guides.
• Stay up-to-date with the latest trends in ML compilers and hardware advances.

Required Qualifications

• BS in Computer/Electrical Engineering or Computer Science with 10+ years of experience; or MS with 8+ years; or PhD with 5+ years of relevant experience (preferred).
• Strong background in compiler design and optimization techniques.
• Experience in developing and optimizing software for high-performance computing systems.
• Experience with LLVM/MLIR is a plus.
• Familiarity with frameworks such as PyTorch, TensorFlow, or JAX.
• Understanding of hardware architectures including CPUs, GPUs, TPUs, and NPUs.
• Strong analytical and problem-solving skills.
• Excellent communication and interpersonal skills with an ability to work both independently and as part of a team.
• Inclusive, adaptive, and passionate about learning and innovation.