Senior Staff Engineer: Shorts Ranking & Core Modeling

Google; Mountain View (CA); On-site; USD 262,000 - 365,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Google's Senior Staff Engineer for YouTube Shorts Ranking in Mountain View leads model development and optimization of the shorts feed, collaborating across ML, data, and product teams to deliver high-quality recommendations.

The role emphasizes ownership of outcomes, architecture design, and cross‑functional leadership to scale solutions for billions of user interactions in a fast-paced, innovative environment.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 7 years of experience leading technical project strategy, ML design, and working with industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with design and architecture; and testing/launching software products.
• 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production.
• Experience building architecture in different modeling domains.

Responsibilities

• Bring ideas to optimize shorts feed for better user experiences, new use cases, and overall product quality.
• Build large-scale machine learning models, training infrastructure and quality evaluation, design ML architecture.
• Work with data scientists, product managers, front-end engineers, user experience designers to improve product quality.

Skills

ML design

Recommendation systems

Distributed systems

Leadership

Project strategy

Software development

Education

Bachelor's degree

Master’s degree or PhD

Job description

Google's Senior Staff Engineer for YouTube Shorts Ranking in Mountain View leads model development and optimization of the shorts feed, collaborating across ML, data, and product teams to deliver high-quality recommendations.

The role emphasizes ownership of outcomes, architecture design, and cross‑functional leadership to scale solutions for billions of user interactions in a fast-paced, innovative environment.