Machine Learning Staff Software Engineer, Search Personalization
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Machine Learning Staff Software Engineer, Search Personalization Share: Share
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Location: Mountain View, CA, USA
Experience Level: Advanced
Advanced experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.
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Minimum 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 (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.
- 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 models.
- 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.
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 them, 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 Salary: $207,000 - $300,000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- 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 real-time 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.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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. based on an agreement concluded between you and Alphabet Inc.
Alphabet
Inc. is your sole contractual partner concerning 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.
Locations: Mountain View, CA, USA
Experience Level: Advanced
Advanced experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in the domain.
Interested in this role?