Senior Staff Tech Lead: TPU Onboarding & Optimization

Google LLC; Singapore; On-site; SGD 210,000 - 420,000; Full time

Job summary

Google LLC is seeking a Senior Staff Tech Lead Manager to drive TPU workload onboarding and optimization for training and serving workloads. You will lead onboarding frameworks, collaborate with ML research and performance teams, and deliver scalable TPU-based solutions for customers.

As part of Google’s AI Engine and Infrastructure, you will mentor engineers, set technical direction for large-scale ML pipelines, and oversee deployment across multiple sites.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience with software development.
• 5 years leading ML design and optimizing ML infrastructure.
• 2 years of experience with state of the art training and inference techniques.
• 2 years of experience in a people management or team leadership role.

Responsibilities

• Act as a Senior Software Manager leading onboarding for stable stack and optimization for training and serving solutions on the latest TPU NPIs.
• Collaborate with the ML research, ML performance, model optimization tooling, and other optimization teams.
• Ship stable stack to our customers for training/inference optimization solutions on TPU.
• Prepare and optimize very large reference models, demonstrating state of the art single‑host and multi‑host inference solutions.
• Work closely with customers to onboard their workloads to production and optimization.

Skills

Software development

Leadership

ML design

ML infrastructure

Model deployment

Model evaluation

Data processing

Debugging

Fine tuning

Team leadership

People management

Education

Bachelor’s degree

Master’s degree or PhD

Job description

Google LLC is seeking a Senior Staff Tech Lead Manager to drive TPU workload onboarding and optimization for training and serving workloads. You will lead onboarding frameworks, collaborate with ML research and performance teams, and deliver scalable TPU-based solutions for customers.

As part of Google’s AI Engine and Infrastructure, you will mentor engineers, set technical direction for large-scale ML pipelines, and oversee deployment across multiple sites.