Lead and deliver production-grade machine learning products from end to end to make Samsung Ads a key player in the mobile ads market.
Design, develop and deploy state-of-the-art and scalable machine learning models to achieve different optimization goals, such as ads click (pCTR), app-install optimization, ROAS optimization, retention, etc.
Research the latest machine learning technologies with industry trends, create prototypes of new ML solutions quickly, and deploy the solution into production.
Analyze complex problems with massive advertising data, identify gaps, and propose and execute technical proposals.
Closely work with different internal ML teams (e.g., ML platform, ML serving, and MLOps teams) to improve our codebase and product health.
Closely work with cross-functional partner teams in global settings to deliver new ML features and solutions and achieve business objectives.
Mentor junior engineers and provide technical guidance.
Learn quickly and adapt to a fast-paced working environment.
Experience Requirements:
Master’s or PhD degree in Computer Science or related fields.
4+ years of industry experience with a Master’s degree or 2+ years of industry experience with a PhD degree.
Solid theoretical background in machine learning and/or data mining.
Proficiency in mainstream ML libraries (e.g., TensorFlow, PyTorch, Spark ML, etc.).
Hands-on experience with production-grade machine learning solutions.
Experience with mainstream big data tools (e.g., MapReduce, Spark, Flink, Kafka, etc.).
Extensive programming experience in Python, Go or other OOP languages.
Familiarity with data structures, algorithms and software engineering principles.
Proficiency in SQL and databases.
Strong communication and interpersonal skills to drive cross-functional partnerships.
Preferred Experience Requirements:
Publications in top relevant venues (e.g., TPAMI, NeurIPS, ICML, ICLR, KDD, WWW, SIGIR, AAAI, IJCAI, etc.).
Basic knowledge about Amazon Web Services (AWS).
Experience with the advertising industry and real-time bidding (RTB) ecosystem.