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Salary
≈ $146k – $270k per year (Estimated)
Location
In office (San Jose)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Sep 26, 2026. First seen by Alion on Apr 14, 2025.

Overview
Company
Impact
Profile match
TikTok is a short-form video platform owned by the Chinese technology group ByteDance and launched internationally in 2016, growing further after the 2018 merger with the lip-sync app Musical.ly. Its recommendation feed surfaces content by engagement signals rather than social graph, which lets new creators reach large audiences quickly and made the app one of the most downloaded in the world. The company runs dual operating hubs in Singapore and Los Angeles and has built an advertising business, a live streaming economy and the TikTok Shop commerce marketplace on top of the video feed.

岗位职责 / Responsibilities

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.

任职要求 / Requirements

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.

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