ML Software Engineer - TPU Training & Inference Optimizer

Google Inc.; Santo Niño 1st; On-site; PHP 1,200,000 - 1,800,000; Full time

Job summary

Google’s AI and Infrastructure team is redefining what’s possible by delivering AI and Infrastructure at scale, reliability and velocity. We empower Google customers and billions of users worldwide with breakthrough capabilities across ML training, inference, and cloud services.

As a software engineer on the ML and infrastructure platform, you will contribute to training/inference workloads, optimize serving on Cloud GPUs/TPUs, and collaborate on system-wide design reviews to push the boundaries

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of software development experience in one or more programming languages, or 1 year with an advanced degree.
• 1 year leading ML design and optimizing ML infrastructure (training, evaluation, data processing, debugging, fine tuning).
• 1 year of experience with training and inference techniques (Megatron-LM, DeepSpeed) and inference techniques (TensorRT-LLM, vLLM, SGLang).

Responsibilities

• Act as ML software engineer leading the onboarding for stable stack, and optimization for training and serving solutions on the latest TPU NPIs.
• Possess extensive technical knowledge of firmware design, kernel development, and server system integration, with the ability to influence the ecosystem.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Lead the server software design, development, and implementation on a scalable and high-quality Cloud Server Program, overseeing the project from conception to launch.

Education

Bachelor's degree or equivalent

Job description

Google’s AI and Infrastructure team is redefining what’s possible by delivering AI and Infrastructure at scale, reliability and velocity. We empower Google customers and billions of users worldwide with breakthrough capabilities across ML training, inference, and cloud services.

As a software engineer on the ML and infrastructure platform, you will contribute to training/inference workloads, optimize serving on Cloud GPUs/TPUs, and collaborate on system-wide design reviews to push the boundaries