Staff AI/ML Software Engineer — Scale LLMs on GCP

Google LLC; Sunnyvale (CA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid time off

Sick time

Maternity leave

Baby bonding leave

holidays

Job summary

Google LLC is seeking a seasoned software engineer for Google Cloud who will develop and optimize large-scale ML systems. The role emphasizes applied ML, LLMs and scalable AI across TPU/CPU/GPU runtimes, with opportunities to lead technical directions and collaborate across teams.

The position involves in-depth work on MaxText and distributed LLM training, delivering high-impact AI features while advancing performance across Google Cloud platforms.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 2 years of experience with Applied Machine Learning (ML), including the development and deployment of models.
• Experience with Large Language Models (LLMs), NLP, or Generative AI.

Responsibilities

• Help make MaxText the best pre and post training solution for TPUs on GCP.
• Implement LLM modeling and scaling techniques in MaxText, including multi-modal, Physical AI and World models.
• Build and support JAX and its ecosystem to benefit GCP customers.
• Support new accelerator introductions (TPUs/GPUs) on GCP and MLPerf submissions that demonstrate cutting edge technologies for Gen AI workloads at scale.
• Work closely with product managers and partner teams to deliver high-quality software products and features throughout their lifecycle.

Skills

Bachelor’s degree or equivalent

8 years software development

Applied ML (2 years)

LLMs, NLP, Generative AI

Technical leadership (3 years)

Performance optimizations for ML

Education

Master’s or PhD in Engineering/CS or related

Job description

Google LLC is seeking a seasoned software engineer for Google Cloud who will develop and optimize large-scale ML systems. The role emphasizes applied ML, LLMs and scalable AI across TPU/CPU/GPU runtimes, with opportunities to lead technical directions and collaborate across teams.

The position involves in-depth work on MaxText and distributed LLM training, delivering high-impact AI features while advancing performance across Google Cloud platforms.