Senior ML Engineer - Lead Cloud ML Training

Google; Town of Montana (WI); On-site; USD 262,000 - 364,000; Full time

Benefits offered by this job

Health/dental/vision

401(k) match

Paid time off

Sick time

Maternity leave

Baby bonding leave

Holidays

Job summary

Google is seeking a Senior Staff Software Engineer to lead ML training initiatives for large-scale cloud models. Based in Kirkland/Seattle areas, you will own ML framework design, training pipelines, and system-level performance for LLMS and diffusion workloads.

Expect leadership across teams and substantial impact on Google Cloud AI capabilities. You will guide architecture, drive robust ML infrastructure, and collaborate with product teams to deliver scalable solutions.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of software development experience (Python).
• 7 years leading technical project strategy, ML design, and working with ML infrastructure.
• 5 years with one or more: speech/audio, reinforcement learning, ML infrastructure, or ML field specialty.
• 5 years of design and architecture; testing/launching software products.

Responsibilities

• Build and deliver ML frameworks to perform training at LLMS and stable diffusion models for Google Cloud customers.
• Design and implement AI frameworks software for ML workloads in the cloud for language modeling, stable diffusion, rankings, and recommendations.
• Identify and resolve issues in software, performance, and topology.
• Work closely with software engineers, product managers, and other engineering teams to deliver high-quality products and features.
• Design, develop, test, deploy, maintain, and improve software.

Skills

Python

ML design

Model deployment

Leadership

Education

Bachelor's degree

Master's degree

Tools

PyTorch

JAX

GCP

GKE

Job description

Google is seeking a Senior Staff Software Engineer to lead ML training initiatives for large-scale cloud models. Based in Kirkland/Seattle areas, you will own ML framework design, training pipelines, and system-level performance for LLMS and diffusion workloads.

Expect leadership across teams and substantial impact on Google Cloud AI capabilities. You will guide architecture, drive robust ML infrastructure, and collaborate with product teams to deliver scalable solutions.