Senior Ads Infrastructure Architect
1 day ago
Senior Ads Infrastructure Architect
About the Company:TikTok is a leading destination for short-form mobile video, with its global headquarters in Los Angeles and Singapore. The company's mission is to inspire creativity and bring joy to users worldwide.
Estimated Salary:$180,000 - $250,000 per year
Job Description:The ads system at TikTok operates on a massive scale, serving millions of advertisers and clients globally. We are looking for an innovative Senior Software Engineer to join our team, providing technical leadership to key projects and empowering the team to build highly efficient infrastructure for collecting and processing data for machine learning training, serving, and privacy enforcement.
Responsibilities:- Lead projects committed to building and operating scalable and reliable ads ranking infrastructure systems
- Develop, drive, and execute the technical vision and roadmap for the ads ML infrastructure team
- Provide technical leadership and guidance to team members and project peers
- Communicate cross-functionally across various teams, organizations, and internal and external stakeholders to drive engineering efforts
- Bachelor's degree in computer science or related technical disciplines
- Hands-on experience with building and training complex and scalable machine learning systems
- Strong Computer Science fundamentals (algorithms, data structures, software design) and problem-solving skills
- Solid coding skills and a good understanding of algorithms, especially causal inference, uplift model, and deep learning
- Experience in managing projects
We are committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe, and so does our workplace. At TikTok, we believe in inspiring creativity and bringing joy to our users.
About the Team:The Ads machine learning data platform team is responsible for building highly efficient infrastructure to collect and process data for the usage of machine learning training, serving, and privacy enforcement, including feature engineering, feature store, training data generation, etc.
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