Experienced Software Engineer - Traffic Platform

About the position

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content. Creation is the core of ByteDance's purpose. Our products are built to help imaginations thrive. This is doubly true of the teams that make our innovations possible. Together, we inspire creativity and enrich life - a mission we aim towards achieving every day. To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At ByteDance, we create together and grow together. That's how we drive impact - for ourselves, our company, and the users we serve. Join us. The Traffic Infrastructure Global Engineering (TIGE)-Traffic Platform team at ByteDance builds and operates multi-cloud based large scale network services around the world that we use to accelerate and optimize network traffic for Tiktok and a variety of application services for ByteDance internal customers, which include but are not limited to layer 4 loadbalancing, layer 4/7 acceleration, global ingress, CMAF, FaaS and WAF, etc. By joining us, you can work within a brilliant team and learn how to build Tiktok scale network traffic platform which serves billions of users globally.

Responsibilities

• Design and develop features of traffic software (DNS Server, L4 and L7 Proxy, Web Caching, and FaaS Runtime), integrate based on our traffic platform to process terabyte-scale data in real-time
• Build data pipeline and develop telemetry systems to support data-driven traffic control
• Develop API acceleration and other networking services that run on top of our multi-cloud based traffic platform
• Problem solving and performance tuning for online traffic
• Research new technologies for more efficient and scalable traffic processing