Staff AI/ML Engineer - Cloud & LLMs

Google LLC; Kirkland (WA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

401(k)

Employer match

Paid time off

Sick time

Maternity leave

Baby bonding leave

Holidays

Job summary

Google Cloud is seeking a software engineer with deep ML/AI experience to help advance MaxText and its JAX ecosystem on Google Cloud Platform. The role focuses on building scalable training and inference stacks, optimizing for CPUs, GPUs, and TPUs, and collaborating with product teams to deliver high-quality software across the full stack.

The candidate should bring a strong background in distributed systems and AI model deployment, with a willingness to own projects end-to-end and contribute to

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

• Learn more about benefits at Google.
• 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

Software development

Applied ML

LLMs

NLP

Education

Bachelor’s degree or equivalent

Master’s degree or PhD preferred

Tools

Large Language Models (LLMs)

NLP

Job description

Google Cloud is seeking a software engineer with deep ML/AI experience to help advance MaxText and its JAX ecosystem on Google Cloud Platform. The role focuses on building scalable training and inference stacks, optimizing for CPUs, GPUs, and TPUs, and collaborating with product teams to deliver high-quality software across the full stack.

The candidate should bring a strong background in distributed systems and AI model deployment, with a willingness to own projects end-to-end and contribute to