Senior Staff ML Engineer - Large-Scale Training & LLM Systems

Google LLC; Sunnyvale (CA); On-site; USD 262,000 - 364,000; Full time

Benefits offered by this job

Health, dental, vision, life, and DIS

401(k) with company match

Paid time off 20 days/year

Sick time 40 hours/year (Seattle 69)

Maternity leave 28-30 weeks

Baby bonding leave 18 weeks

13 paid holidays

Job summary

Google LLC is seeking a Senior Staff Software Engineer (ML Training) to lead development of ML training frameworks at scale, including LLMs and diffusion models, on Google Cloud. You will guide ML infrastructure, model deployment, data processing, and performance optimization.

You will work with multiple teams to shape ML architectures, ensure reliability, and deliver end-to-end software solutions that scale for customers globally. Familiarity with GCP tools and cloud-native design is essential.

Qualifications

• 8 years of experience in software development (e.g., Python).
• 7 years of experience leading technical project strategy, ML design, and ML infrastructure.
• 5 years of experience with speech/audio, reinforcement learning, ML infrastructure, or related ML field.
• 5 years of experience with design and architecture; testing/launching software products.

Responsibilities

• Build and deliver ML frameworks to perform training for LLMs and diffusion models in Google Cloud customers.
• Design and implement AI software for ML workloads in the cloud enabling language modeling, diffusion, rankings, recommendations.
• Identify and resolve issues in software performance and topology.
• Collaborate with engineers, PMs, and teams to deliver high-quality products through the lifecycle.
• Design, develop, test, deploy, maintain, and improve software.

Skills

Python

ML design

Leadership

Education

Bachelor’s degree or equivalent practical experience

Master’s degree or PhD in Engineering/CS

Tools

GCP

Kubernetes

PyTorch

JAX

Job description

Google LLC is seeking a Senior Staff Software Engineer (ML Training) to lead development of ML training frameworks at scale, including LLMs and diffusion models, on Google Cloud. You will guide ML infrastructure, model deployment, data processing, and performance optimization.

You will work with multiple teams to shape ML architectures, ensure reliability, and deliver end-to-end software solutions that scale for customers globally. Familiarity with GCP tools and cloud-native design is essential.