Machine Learning Engineer (머신러닝 엔지니어)

About Moloco: Moloco is an AI-native performance advertising company, bringing the power of AI advertising to the open internet. Founded in 2013 by machine learning engineers who had built AI advertising systems inside the world's largest technology companies, Moloco began from a shared mission: to build that same engine for the open internet. Today, Moloco is one company with two businesses, built on the same compound AI system. Moloco Ads is our AI-native performance advertising platform, helping mobile app marketers acquire, retain, and re-engage high-value users across the open internet. Moloco Commerce Media is our AI-native retail media platform, enabling retailers and marketplaces to turn their platforms into thriving ad businesses. Both are powered by CARA (Compound Ad Recommendation Architecture) , the AI system behind every Moloco product. At Moloco, we bring together those who've already solved hard problems and those with the drive to. Here, we work on some of the complex problems in AI advertising, at a scale and level of sophistication very few companies can offer. Come build what's next. About the Role We seek exceptional machine learning engineers to join us in building a state-of-the-art machine learning system. Moloco's ML system processes over 6 million bid requests per second at under 7ms prediction latency, and our deep learning models power CTR/CVR prediction, ranking, and bid price optimization for live auction decisions at planet scale. Moloco is an engineering company founded by top-tier engineers, and machine learning is the core of Moloco's engineering systems. We understand the value of a strong engineering team and strive to hire only the best engineers. As a Machine Learning Engineer, you will contribute to the full machine learning lifecycle — from model development and experimentation to data pipeline maintenance and production deployment. This role is designed for engineers who have solid machine learning and software engineering fundamentals, can execute end-to-end tasks with increasing independence, and are eager to grow through hands-on work in one of the most technically demanding real-time ML environments in the industry. What You Will Do Develop and iterate on deep learning models for real-world prediction problems, including CTR/CVR estimation and ranking, with guidance on modeling choices and objective function design. Build and maintain data pipelines for model training and serving using GCP products such as Dataflow, BigQuery, BigTable, and open-source frameworks such as Apache Beam, PySpark, and Iceberg. Support production model serving, monitor model behavior in live environments, and contribute to debugging and improving model quality. Design and run offline experiments — define evaluation metrics, test hypotheses, and document findings to contribute to team-level modeling decisions. Collaborate with fellow Machine Learning Engineers, Applied Scientists, and Infrastructure engineers to deliver projects end-to-end within defined scopes. Grow your understanding of Moloco's AdTech domain — including auction mechanics, bidding systems, and advertising outcome modeling — and apply that context to your work. Basic Qualifications (3 Titles) Machine Learning Engineer II Bachelor's degree or higher in Computer Science or a related technical field, or equivalent professional experience. 2+ years of hands-on software development experience in machine learning or deep learning, with at least some exposure to production systems beyond academic or personal projects. Working knowledge of core machine learning modeling concepts, including classification and regression model selection, loss function design, bias/variance trade-offs, calibration, and offline evaluation. Solid foundation in statistics and probability, including conditional probability, common distributions, maximum likelihood estimation, hypothesis testing, and basic A/B test interpretation. Experience building or contributing to data pipelines or model serving systems, with an understanding of the engineering trade-offs involved. Proficiency in at least one programming language such as Python, Java, or Go. Fluent English communication skills. Senior Machine Learning Engineer Bachelor's degree or higher in Computer Science or a related technical field, or equivalent professional experience. 5+ years of hands-on software development experience in machine learning and deep learning, with a clear focus on production systems rather than research prototyping. Strong machine learning modeling depth, including model selection for classification, regression, and ranking, loss function design, calibration, class imbalance handling, and bias/variance trade-off reasoning. Solid foundation in statistics and probability, including Bayesian inference, maximum likelihood estimation, hypothesis testing, A/B experiment design and interpretation, and probabilistic reasoning under