Senior Software Engineer, Ranking Engineering
TikTok
San Jose, CA · Posted November 13, 2026
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November 2026
- #1Best cities for marketing pay after cost of living$204k · of 16
- #1Best cities for aerospace and defense pay after cost of living$187k · of 19
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- #5Best cities for technology jobs1,449 openings · of 100
- #5Cities with the most jobs that do not need a four-year degree in the West Coast162 jobs · of 47
Rankings about engineering jobs
- 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)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
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Pay compared with the market
This listing does not state pay. Across 615 open senior software engineer listings that state pay, the middle half runs $170,500 to $222,000 and the median is $199,000.
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How AI is used in this kind of work
Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
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
About The Team TikTok’s recommendation system is at the core of our user experience, delivering personalized content to millions of users in real time. Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for our recommendation system to provide the most stable and best experience for our TikTok users.
What you will be doing: - Architect, build, and optimize large-scale ranking systems that serve billions of daily recommendations with low latency and high precision. - Design flexible, efficient, and scalable ranking frameworks to support evolving machine learning models and features. - Collaborate with ML engineers to integrate ranking models into production, ensuring seamless inference, freshness, and feedback loops. - Analyze system bottlenecks and apply performance optimizations at the framework and infrastructure level (CPU/GPU, memory, storage, networking). - Drive technical excellence and best practices in software design, code quality, and system reliability.
Minimum Qualifications: - Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field. - Experience in building large-scale recommendation, ranking, or search systems. - Experience in C++, Go, or Python, and with distributed computing frameworks. - Solid understanding of ranking algorithms, machine learning inference systems, and system performance optimization.
Preferred Qualifications: - Experience in machine learning platform infrastructure, particularly online prediction serving or ranking pipelines. - Familiarity with feature engineering pipelines, model lifecycle management, and A/B testing systems. - Experience working with multi-threading, memory management, and low-latency service architectures. - Proven ability to lead complex projects across multiple teams and stakeholders.