Software Engineer, TikTok Brand Ads

The Brand Ads Team builds technologies that unlock business growth potential. This team owns several ads products: reservation ads, auction ads, and innovative content ads that enables advertisers and users to foster more awareness of their brand to attain their business goals. We work on the end-to-end ads delivery tech stack, including ads bidding, ranking, and forecasting. We are looking for experienced engineers that have strong problem solving skills and algorithm understanding to build and manage systems with high performance, scalability, and availability. You will have the opportunity to partner closely with a globalized engineering and product teams in a high-impact and fast-paced environment. Responsibilities: • Create innovative monetization products that drive engagement and business outcomes. • Develop highly scalable services that powers new ad products for billions of requests. Design systems that will optimize monetization efficiency with product engineering and state-of-the-art machine learning technologies. • Implement new ad solutions that will continuously protect the user experiences on TikTok. • Collaborate with strategy team, product managers, and other key stakeholders to define products and drive initiatives from engineering perspective. • Contribute to the success of a rapidly growing and evolving organization with speediness and quality. Minimum Qualifications: - BS degree in Computer Science, Computer Engineering or other relevant majors with 3+ year of work experience. - Excellent programming, debugging, and optimization skills in one or more general purpose programming languages including but not limited to: Go, C/C++, Python. - Proficient in the mechanics of computational advertising, with a strong understanding of ad delivery systems. - Ability to think critically and to formulate solutions to problems in a clear and concise way. Preferred Qualifications: - Good understanding in one of the following domains: brand ads, content ads, auction, bidding, ranking, and ads forecasting. - Good knowledge in one of the following areas: machine learning, deep learning, backend, large-scale systems, data pipeline. - Good product sense and experience designing and implementing product features.