이 공고, 이렇게 물어볼 겁니다
공고 내용
About Moloco:
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 uncertainty.
- Dem
회사마다 모든 공고에 똑같이 붙는 안내 문구(지원 절차·서류 반환·개인정보 고지 1,106자)는 접어뒀어요. 원문에서 전체 보기 →
원문에서 전체 공고 보기 →