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Alphabet · Mountain View, CA

# Tech Lead, YouTube Shorts Discovery, ML Recommendations

Mountain View, CA, USA Manager or lead 

Listed on Alphabet’s official careers site. Listed as of October 23, 2026. Check that it is still open and apply there.
[Apply on Alphabet’s careers site →](https://www.google.com/about/careers/applications/jobs/results/98663124952851142-tech-lead-youtube-shorts-discovery-ml-recommendations)

[OpenNash Jobs](https://jobs.opennash.com/) / [Alphabet](https://jobs.opennash.com/companies/alphabet/) / Tech Lead, YouTube Shorts Discovery, ML Recommendations

## Job description

info_outline 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 a glance
- Posted by the employer: Not stated
- First seen by OpenNash: Oct 13, 2026
- Last checked: Oct 23, 2026
- Listed for: 10 days
- Location: Mountain View, CA, USA[Apply on Alphabet’s careers site →](https://www.google.com/about/careers/applications/jobs/results/98663124952851142-tech-lead-youtube-shorts-discovery-ml-recommendations)

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