Back
Strong employer brand and metro location increase competition despite niche ML compiler specialization.
Highly specialized ML compiler and accelerator expertise limits transferability across industries.
Explicit 8+ years requirement and specialized compiler/TPU/C++ skills make filters strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Drive continuous improvement and performance optimization of the TPU compiler and ML software/hardware stack for Google first-party and Google Cloud Platform customers.
Design and implement advanced compiler optimizations (e.g., pipelining, prefetching, fusions) to maximize TPU efficiency and impact large-scale projects like LLM development and chip co-design.
Collaborate with multiple teams to integrate ML frameworks such as PyTorch and provide technical leadership and mentorship as a Team Lead on strategic initiatives.
Bachelor's degree or equivalent practical experience.
8 years of experience in software development and 3 years in software design and architecture.
Required skills include machine learning, compilers, computer architecture, GPU programming, C++, and Python.
Work Experience Required: Minimum 8 years in software development as explicitly mentioned.
Deep experience with state-of-the-art ML compilers, including writing compiler optimization passes and open-source software development.
Strong understanding of accelerator hardware architectures like TPUs and GPUs, with hands-on performance analysis and debugging skills across the ML software stack.
Proven ability to provide technical leadership and mentor teams, with a strategic outlook on compiler optimizations impacting both internal Alphabet initiatives and external cloud users.