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Tech Lead, YouTube Shorts Discovery, ML Recommendations

Google

Mountain View, CAJob$207–300K/yrSeen 2w 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

The Tech Lead will guide YouTube Shorts discovery and recommendation work, helping build personalized recommendations and LLM-based recommendation systems. The role focuses on finding initial audiences for fresh videos and growing the recommendable video corpus. It provides technical leadership across high-impact projects, aligns teams on goals and timelines, and leads specialized machine learning solutions and large-scale software development.

Skills & qualifications

RequiredNice to have

Skills

Software DevelopmentSoftware TestingSoftware LaunchSoftware DesignSoftware ArchitectureSpeech/AudioReinforcement LearningMachine LearningML DesignML InfrastructureData StructuresAlgorithmsDistributed SystemsLarge-Scale ML SystemsTechnical LeadershipRecommendation SystemsPersonalized RankingRetrieval SystemsCold-Start ManagementExploration/Exploitation Algorithms

Qualifications

Bachelor's Degree or Equivalent Practical Experience8 Years Software Development5 Years Testing and Launching Software3 Years Software Design and Architecture5 Years ML or Speech/Audio Experience5 Years ML Design and InfrastructureMaster's or PhD in CS or Related8 Years Data Structures and Algorithms3 Years Technical LeadershipEnglish Proficiency

Full job description

Tech Lead, YouTube Shorts Discovery, ML Recommendations

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corporate_fare YouTube 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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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 testing, and launching software products, and 3 years of experience with software design and architecture.

  • 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), or specialization in another ML field.

  • 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

Preferred qualifications:

  • Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related technical field.

  • 8 years of experience in data structures and algorithms, with experience building distributed, large-scale machine learning systems.

  • 3 years of experience in a technical leadership role, defining technical goals, setting roadmap direction, and mentoring executive engineering teams.

  • Experience designing and deploying recommendation systems, personalized ranking models, or retrieval systems.

  • Expertise in managing the cold-start problem, reinforcement learning, or exploration/exploitation algorithms.

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.

The Short-form Video team owns everything from the mobile creation experience and related mobile effects (e.g., text, stickers, filters) , through a new video player experience that provides full screen videos with a quick tap to see the next videos, and through all the backend systems to allow creating and serving these videos and recommending them to users on home, search, and more.

Shorts exploration is a critical part of shorts recommendation with the mission to find an initial audience for fresh videos to enlarge our recommendable corpus and to inspire creation. We leverage various modeling techniques and signals to build initial audiences for fresh videos within the recommendation stack.

At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun and we do it all together.

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

  • Contribute to personalized quality recommendations and help build and grow a promising new product within Google, focusing on the discovery/recommendation engine and LLM-based recommendation systems.

  • 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.

  • Lead the design and implementation of solutions in specialized ML areas, optimize ML infrastructure, and guide the development of model optimization and data processing strategies.

  • Design, develop, test, deploy, maintain, and enhance large scale software solutions.

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 6,158 open Machine Learning Engineer jobs on Olive Jobs, counted October 28, 2026.

Pay
  • This posting$207–300K/yr
  • California median$174–260K/yr1,348 salary ranges
  • US median$144–242K/yr4,913 salary ranges

This range's midpoint, $254K, is 17% above the California median midpoint ($218K) — in the middle half of Machine Learning Engineer salary ranges in California.

Openings
Olive Jobs lists 1,822 open Machine Learning Engineer jobs in California and 6,158 across the US. 7% 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 4,916 postings).
Education
2,538 of the 6,158 open Machine Learning Engineer jobs (41%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on October 28, 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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