Machine Learning Staff Software Engineer, Search Personalization

Google LLC; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Benefits offered by this job

Bonus target 20%

Equity

Job summary

Google LLC in Mountain View, CA, is seeking a Machine Learning Staff Software Engineer for Search Personalization. You will design and deploy personalized user models, scale ML systems to billions of users, and drive end-to-end ML projects from design to launch.

The role emphasizes leadership, innovation, and collaboration across teams. Applicants should have a BS/equivalent, 8 years in software development, and 5 years in recommender systems, ML infrastructure, and product deployment.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of software development experience.
• 5 years building and deploying recommender systems models in production.
• 5 years ML design and ML infrastructure experience.
• 5 years testing and launching software products; 3 years design/architecture.

Responsibilities

• Design and implement personalized user models to optimize for user happiness.
• Build user and content clustering models for personalization and ranking.
• Enhance model performance with advanced modeling techniques and feature engineering.
• Scale applications across modalities and use cases for billions of users.
• Create next-generation realtime ML models and scalable training/serving pipelines.

Skills

Software development

Recommendation systems

ML design & infrastructure

Testing & launch

Software design & architecture

Education

Bachelor’s degree or equivalent

Tools

C++

Dremel/F1

TensorFlow

Job description

Machine Learning Staff Software Engineer, Search Personalization

Share Machine Learning Staff Software Engineer, Search Personalization

corporate_fare Google Mountain View, CA, USA

X In most instances, this position requires in-person interviews as part of the hiring process.

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience building and deploying recommendation systems models (retrieval, prediction, ranking, embedding) in production and experience building architecture in different modeling domains.
• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.

Preferred qualifications:

• 8 years of experience with data structures and algorithms.
• 6 years of ML or Quality experience working on recommendation systems.
• Experience in recommender systems, clustering algorithms, SQL, deep model.
• Experience in C++, Dremel/F1 and TensorFlow.
• Experience working with research.
• Ability to drive quality projects end-to-end from design to implementation to eventual launch.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.

As a part of the Discover Personalization team, you will help people feel positively connected and informed about the world around them by delivering the pulse of the Internet that matters to you, within Google Search. You will contribute to the key product's appeal, which lies in having an understanding of users and will be laser focused on building foundational user models for users using all of their interactions across Google products, and leveraging them to power Discover’s retrieval and ranking. You will manage some of the toughest ML and Quality problems, including Neural Deep Retrieval, Activity Clustering, Reinforcement Learning and Multi-Objective Ranking.

In Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google .

• Design and implement personalized user models to optimize for user happiness, including Neural Deep Retrieval Models, Deep Neural Network Ranking/Scoring models, User/Content Clustering Models, Large Language Models (LLM)-based Retrieval Augmented Generation Models, and more.
• Build user and content clustering models to enable core personalization and ranking use cases.
• Enhance model performance and personalization precision/recall through advanced modeling techniques such as transformers, distillation, reward shaping, multi-task learning, neural bandits, etc. and capabilities through feature engineering, automatic parameter tuning, label quality engineering, etc.
• Scale the model's applications to a multitude of modalities (content, queries, videos and notifications) and use cases (retrieval, ranking, content generation, diversification, etc.).
• Create next-generation realtime ML models that can capture new user interests and world trends in seconds and scale model training and serving to billions of users.

Google is proud to be an equal opportunity and affirmative action employer.

We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.

See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.