Senior TPU ML Compiler Engineer

Socket.dev; New York (NY); On-site; USD 207,000 - 300,000; Full time

Job summary

Google is seeking software engineers to build the Accelerated Linear Algebra (XLA) compiler for TPUs, accelerating ML workloads for internal and Cloud customers. You will design, develop, test, and deploy compiler solutions across a range of TPU generations and workload types.

You will collaborate with hardware teams to co-design future processors and optimize performance on large-scale distributed systems, with responsibilities spanning end-to-end software development and system-level debugging.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience programming in C++ or Python.
• 5 years of experience testing, and launching software products.
• 5 years of experience with performance, large-scale systems data analysis, visualization tools, or debugging.
• 3 years of experience with software design and architecture.

Responsibilities

• Contribute to the compiler for a novel processor designed to accelerate machine learning workloads.
• Target and compile high-performance implementations of operations at distributed scale.
• Design and implement new compiler passes that extract more performance out of current and next-generation TPUs, directly impacting fleet efficiency.
• Collaborate closely with hardware designers to co-design future processors.
• Research high-level representations to effectively program large-scale, distributed, and heterogeneous systems.

Skills

C++

Python

Software testing

Software design

Software architecture

ML compilers

Compiler optimization

Debugging

TPU/GPUs

Education

Bachelor's degree or equivalent practical experience

Tools

N/A

Job description

Google is seeking software engineers to build the Accelerated Linear Algebra (XLA) compiler for TPUs, accelerating ML workloads for internal and Cloud customers. You will design, develop, test, and deploy compiler solutions across a range of TPU generations and workload types.

You will collaborate with hardware teams to co-design future processors and optimize performance on large-scale distributed systems, with responsibilities spanning end-to-end software development and system-level debugging.