Tech Lead - E-commerce Recommendation Infrastructure - San Jose
TikTok
San Jose, CA · Posted November 13, 2026
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November 2026
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- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
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TikTok has filed one layoff notice in the last twelve months, covering 250 workers, most recently August 2026. These are public filings with state labor departments, and an open role can sit alongside them. See the filings
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About the job
Our Team E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. Our E-commerce Recommendation Infra team is responsible for building up and optimizing the infrastructure for such recommendation systems, so as to provide the most stable and best experience for our users. We work closely with applied machine learning engineers and build scalable systems to support all kinds of innovative algorithms and techniques.
Responsibilities - Build industry-leading globalized large-scale recommendation system; - Design and build high performance online systems and reliable data pipelines; - Optimize and evolve the system continuously so as to support the skyrocket increase in both user traffic as well as the data amount; - Work with cross functional teams to deliver end-to-end infrastructure solutions to address critical product challenges and improve recommendation performance.
Minimum Qualifications - Bachelor's degree or above, majoring in Computer Science or related fields - At least 5+ years of experience building scalable systems. - Strong software development experience with C++, Java or other programming language; - Good teamwork and communication skills, positive and optimistic, and strong sense of ownership; - Experienced in at least one of the following areas: personalized recommendations, search engine, advertising, machine learning infrastructure, distributed storage system, big data frameworks.