We are a fast-growing technology company redefining digital advertising with innovative, data-driven solutions. Our mission is to empower businesses with a high-performance ad platform that drives exceptional results.
Job OverviewAs a
Machine Learning Engineer
specializing in computational advertising, you will design algorithms for bidding strategies, real-time traffic control, and value estimation. Your work will directly impact ad revenue growth through advanced ML applications in our advertising ecosystem.
Responsibilities1. Algorithm Design & Optimization
Develop intelligent bidding algorithms (e.g., automated bid shading, ROI-based optimization)
Design real-time traffic control and calibration algorithms to stabilize platform economics
Architect auction mechanisms to balance user experience and advertiser value
2. Prediction Modeling
Build high-accuracy models for
Deep conversion event probability (e.g., purchases, app installs)
Implement multi-objective optimization for competing metrics
Apply state-of-the-art ML techniques (causal inference, bandit learning) to ad delivery challenges
Explore LLM applications for creative optimization and audience targeting
Publish novel solutions at top-tier conferences (KDD, WWW, etc.)
QualificationsMust-Have
Master's/PhD in CS, EE, Automation, or related quantitative fields
Strong analytical skills with ability to abstract business problems into ML models
Expertise in machine learning (especially GBDT, DNN, reinforcement learning), operations research/control theory, computational advertising principles
Production-level coding ability (Python/Scala/C++)
Nice-to-have
2+ years experience in DSP/SSP platforms, recommendation/search ranking systems, large-scale distributed ML training
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Job OverviewAs a
Machine Learning Engineer
specializing in computational advertising, you will design algorithms for bidding strategies, real-time traffic control, and value estimation. Your work will directly impact ad revenue growth through advanced ML applications in our advertising ecosystem.
Responsibilities1. Algorithm Design & Optimization
Develop intelligent bidding algorithms (e.g., automated bid shading, ROI-based optimization)
Design real-time traffic control and calibration algorithms to stabilize platform economics
Architect auction mechanisms to balance user experience and advertiser value
2. Prediction Modeling
Build high-accuracy models for
Deep conversion event probability (e.g., purchases, app installs)
Implement multi-objective optimization for competing metrics
Apply state-of-the-art ML techniques (causal inference, bandit learning) to ad delivery challenges
Explore LLM applications for creative optimization and audience targeting
Publish novel solutions at top-tier conferences (KDD, WWW, etc.)
QualificationsMust-Have
Master's/PhD in CS, EE, Automation, or related quantitative fields
Strong analytical skills with ability to abstract business problems into ML models
Expertise in machine learning (especially GBDT, DNN, reinforcement learning), operations research/control theory, computational advertising principles
Production-level coding ability (Python/Scala/C++)
Nice-to-have
2+ years experience in DSP/SSP platforms, recommendation/search ranking systems, large-scale distributed ML training
#J-18808-Ljbffr