Huawei Petal Ads – Senior Ads Bidding Algorithm Scientist

About HuaweiHuawei’s products and services are available in more than 170 countries and are used by a third of the world’s population. ## What you'll do play a pivotal role in shaping the mechanism design, auction dynamics, and traffic dispatch strategies for our next-generation ad exchange platform. Joining a world-class team, you will tackle high-stakes problems in computational advertising, ranging from multi-DSP game equilibrium to latency monetization, sequential causal inference, and anti-fraud modeling. Unlike an applied role, this position requires an expert with both theoretical mastery and hands-on systems experience to bridge theory with large-scale production execution. You will drive innovations that maximize traffic value, optimize advertiser ROI, and safeguard platform health across billions of daily impressions. This is an exceptional opportunity to steer Huawei Petal Ads' global strategy, lead key algorithmic breakthroughs, and set industry benchmarks for intelligent ad trading ecosystems. Responsibilities - Mechanism Design & Global Optimization Lead the architecture and design of the ad platform's auction mechanisms and intelligent dispatching strategies. Construct a dynamic optimization framework integrating traffic allocation, dynamic pricing, and latency control to maximize core monetization efficiency. - Scientific Evaluation Framework & Automated Iteration Establish a scientific and data-driven evaluation powered by hypothesis testing and sequential causal inference. Drive the transition from manual decision-making to automated attribution and experimentation, significantly accelerating online deployment and iteration cycles. - Technical Roadmap & Collaborative Execution Formulate the strategic technical roadmap for mechanism strategies and lead end-to-end algorithm delivery. Drive breakthroughs in multi-DSP game equilibrium, optimal routing, and buyer response/bid prediction models to meet business targets while establishing reusable methodology frameworks. - Anti-Fraud & Risk Control Deepen capabilities in anomaly detection and behavioral sequence modeling to build a dynamic traffic quality system. Enable deep integration with downstream ranking/billing models to achieve synergy between platform health and monetization performance. - Frontier Technology Exploration Explore next-generation billing mechanisms, multi-ADX auction strategies, and distributed control algorithms. Benchmark and integrate global industry-leading ad engine architecture evolutions to build long-term technical reserves and commercial competitiveness. Requirements1. Ph.D. degree (or Master's with exceptional track record) in Reinforcement Learning, Applied Mathematics, Game Theory, Machine Learning, or related fields. 5+ years of experience in ad auction mechanisms, trading strategies, computational economics, or ad tech system co-design. 3+ years of experience leading cross-regional teams or large-scale ad engine algorithms is highly preferred. - Profound mastery of Real-Time Bidding (RTB), game theory, and hybrid auction mechanisms. Deep expertise in resource-constrained optimization, sequential decision-making, DSP response modeling, causal inference, anomaly detection, and adversarial modeling, with a proven ability to translate complex business and risk constraints into solvable mathematical mechanisms. - End-to-end architecture expertise spanning offline simulation, causal attribution, and online A/B testing. Expert in behavioral sequence modeling and deep feature integration for downstream strategies. Track record of driving significant business revenue growth and engine efficiency optimization through mechanism innovation. - Strong strategic mindset and cross-functional communication skills, with the ability to articulate trade-offs in mechanism design and risk ecosystems. Recognized as a technical authority and influential voice within the global academic or industrial AI/AdTech community. …

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