Senior Software Engineer, AI-Driven Personalization & Ranking

Socket.dev; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google is seeking software engineers to help build the world’s most intelligent content recommendation engine and scale AI-driven personalization. You will work on ranking models, retrieval and embedding techniques, and novel discovery paradigms that affect billions of users daily.

You’ll collaborate across teams to advance information retrieval, distributed systems, and ML infrastructure, shaping how users interact with information at scale.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production; and experience building architecture.
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 3 years of experience with data analysis, data manipulation, and statistical methods.

Responsibilities

• Develop and test new ranking algorithms and model features
• Analyze experiment results to measure impact and guide improvements.
• Collaborate with other engineers and researchers to implement new ideas.
• Contribute to the quality and reliability of the ranking systems. Explore new techniques to advance content understanding and personalization.
• Design and implement recommendation systems models across different domains, leverage ML infrastructure, and contribute to architecture design.

Skills

Software development

Testing

ML infrastructure

Data analysis

Education

Bachelor's degree

Tools

Python

C++

Job description

Google is seeking software engineers to help build the world’s most intelligent content recommendation engine and scale AI-driven personalization. You will work on ranking models, retrieval and embedding techniques, and novel discovery paradigms that affect billions of users daily.

You’ll collaborate across teams to advance information retrieval, distributed systems, and ML infrastructure, shaping how users interact with information at scale.