Machine Learning Engineer (머신러닝 엔지니어)

About Moloco:

Moloco builds some of the most powerful AI advertising solutions in the world. Our name—short for "machine learning company"—reflects our core mission: democratizing access to the advanced AI that has historically been reserved for tech giants. Led by machine learning pioneers who built some of the most successful ad systems at Google, including YouTube's monetization engine and key search advertising technologies, we're transforming how businesses grow and compete in the digital economy.

Built with AI from day one, Moloco’s planet-scale machine learning platform powers a suite of solutions for advertising growth and monetization. Moloco Ads is an AI-powered platform that delivers real business outcomes for mobile app marketers through performance-based user acquisition. Moloco Commerce Media enables retailers and marketplaces to build revenue-generating ad businesses that balance user experience and advertiser performance.

Moloco is headquartered in Silicon Valley, with offices in Seattle, New York, San Francisco, Seoul, Beijing, Singapore, Gurgaon, Tokyo, Shanghai, London, Tel Aviv, and Berlin.

Moloco is a truly rewarding place to work and in an exciting period of growth, which you could be a part of. Join us today and apply now!

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,