포지션 상세
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.
• 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.
• 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.
• Demonstrated experience designing and operating large-scale machine learning systems under real-world constraints, including model-serving architectures, feature stores, and training pipelines.
• Proficiency in at least one programming language such as Python, Java, or Go, with the ability to write clean, robust, production-quality code.
• Fluent English communication skills.
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.
주요업무
• 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.
자격요건
• 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.
• Demonstrated experience designing and operating large-scale machine learning systems under real-world constraints, including model-serving architectures, feature stores, and training pipelines.
• Proficiency in at least one programming language such as Python, Java, or Go, with the ability to write clean, robust, production-quality code.
• Fluent English communication skills.
