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Machine Learning Staff Software Engineer, Search Personalization

Google

Mountain View, CAJob$207–300K/yrSeen 1w agoSeen in employer's feed 1 day ago

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At a glance

Compensation
$207–300K/yr
Location
Mountain View, CA
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

Google seeks a staff software engineer for its Discover Personalization team, building foundational user models that power retrieval and ranking in Google Search. The engineer will address machine learning and quality challenges across personalization, clustering, and ranking, and scale real-time model training and serving to billions of users. The role involves managing project priorities and delivering software solutions.

Skills & qualifications

RequiredNice to have

Skills

Recommendation SystemsModel DeploymentModel EvaluationData ProcessingDebuggingFine TuningSoftware TestingSoftware DesignSoftware ArchitectureData StructuresAlgorithmsClustering AlgorithmsSQLDeep LearningC++Dremel/F1TensorFlowEnd-to-End Project DeliveryNeural Deep RetrievalDeep Neural Network RankingUser and Content ClusteringRetrieval Augmented GenerationTransformersKnowledge DistillationReward ShapingMulti-Task LearningNeural BanditsFeature EngineeringAutomatic Parameter TuningLabel Quality Engineering

Qualifications

Bachelor's Degree or Equivalent Practical Experience8 Years Software Development5 Years Recommendation Systems Models5 Years ML Design and Infrastructure5 Years Testing and Launching Products3 Years Software Design and Architecture8 Years Data Structures and Algorithms6 Years ML or Quality Recommendation SystemsExperience Working With ResearchEnglish Proficiency

Full job description

Machine Learning Staff Software Engineer, Search Personalization

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corporate_fare Google place Mountain View, CA, USA

Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.

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info_outline

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

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.

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 aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .

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 realtime ML models that can capture new user interests and world trends in seconds and scale model training and serving to billions of users.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

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 alsoGoogle's EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC\_KnowYourRights\_10\_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .

If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .

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.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.

How this job compares

Set against the 6,153 open Machine Learning Engineer jobs on Olive Jobs, counted November 4, 2026.

Pay
  • This posting$207–300K/yr
  • California median$176–261K/yr1,361 salary ranges
  • US median$148–245K/yr4,910 salary ranges

This range's midpoint, $254K, is 15% above the California median midpoint ($220K) — in the middle half of Machine Learning Engineer salary ranges in California.

Openings
Olive Jobs lists 1,835 open Machine Learning Engineer jobs in California and 6,153 across the US. 8% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 8 years of experience — more than three in four Machine Learning Engineer postings that state a minimum ask for (median 5 years, across 4,893 postings).
Education
2,302 of the 6,153 open Machine Learning Engineer jobs (37%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 4, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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