Senior Staff ML Engineer: Recommendations & Search Discovery

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

Benefits offered by this job

Equity

Bonus target

Benefits

Job summary

Google LLC's Senior Staff Software Engineer role sits within the Discover Ranking and Search Discovery domains, based in Mountain View, CA. The team develops AI-driven content recommendations and scalable systems affecting billions of users.

The role emphasizes leadership across projects, ML infrastructure optimization, and advanced ranking techniques, with opportunities to influence product direction and drive impact at scale.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience building and deploying recommendation systems models in production.
• 5 years of experience with design and architecture; and testing/launching software products.

Responsibilities

• Provide technical leadership on high-impact projects. Manage project priorities, deadlines, and deliverables.
• Facilitate alignment and clarity across teams on goals, outcomes, and timelines. Influence and coach a distributed team of engineers.
• Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of advanced recommendation systems.
• Explore new techniques to advance content understanding and personalization.

Skills

Technical leadership

ML infrastructure

Recommendation systems

Large-scale system design

Distributed computing

English proficiency

Cross-functional collaboration

Education

Bachelor’s degree or equivalent

Master’s degree or PhD preferred

Job description

Google LLC's Senior Staff Software Engineer role sits within the Discover Ranking and Search Discovery domains, based in Mountain View, CA. The team develops AI-driven content recommendations and scalable systems affecting billions of users.

The role emphasizes leadership across projects, ML infrastructure optimization, and advanced ranking techniques, with opportunities to influence product direction and drive impact at scale.