CyberLabo is a revolutionizing AI‑powered gateway that transforms real‑time data into autonomous bidding, predictive targeting, and intelligent optimization—engineered to scale across channels and markets.
Senior Algorithm Engineer
• *About Us: **
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. We’re seeking a highly technical Algorithm Engineer (AI AdTech) to lead the development of our advanced advertising technology suite, working hand-in-hand with engineering and data science teams to deliver cutting-edge solutions.
• *Job Overview: **
As an AI Advertising Algorithm Engineer, you will design and implement core advertising algorithms, including but not limited to CTR/CVR prediction, bidding strategies, intelligent bidding, and audience targeting. You will deeply understand advertising business scenarios, continuously optimize algorithm performance using machine learning and deep learning technologies, and work closely with engineering teams to deploy algorithms into production environments.
Key Responsibilities
Core Advertising Algorithm Development
Research and develop innovative CTR/CVR prediction models, including feature engineering, model architecture design, and training optimization
Develop deep learning-based ad ranking algorithms to optimize core metrics like eCPM
Research and implement intelligent bidding strategies (bid shading, ROI optimization, etc.)
User Understanding & Targeting
Build user profiling systems and develop user embeddings based on representation learning
Develop lookalike expansion algorithms to improve audience targeting accuracy
Optimize real-time audience segmentation and matching efficiency
Algorithm Engineering
Deploy algorithm models to online systems, ensuring stability and performance in high-concurrency scenarios
Develop feature platforms for efficient feature production and reuse
Build A/B testing frameworks to scientifically evaluate algorithm performance
Cutting-edge Technology Exploration
Stay updated on the latest advancements in advertising algorithms (e.g., multi-task learning, causal inference)
Explore applications of large language models in ad creative generation and intelligent delivery
Research the implementation of privacy-preserving technologies in advertising scenarios
Qualifications
Must-Have:
Bachelor’s / Master's degree or above in Computer Science, Mathematics, Statistics, or related fields
3+ years of experience in advertising algorithms, recommendation systems, or search algorithms
Solid foundation in machine learning, familiar with common algorithm principles and implementations
Proficient in Python and familiar with frameworks like TensorFlow/PyTorch
Experience with big data processing tools like Spark/Flink
Deep understanding of advertising business and familiarity with DSP/SSP architectures
Nice-to-Have:
Hands-on experience with large-scale advertising algorithms, familiar with DSP/SSP/RTB ecosystems
Publications in top conferences on advertising algorithms
Familiarity with cutting-edge technologies like reinforcement learning and multi-task learning
Experience in feature platforms and model serving
职位描述:算法工程师(AI广告技术方向)
工作地点: [填写具体地点或远程办公]
雇佣类型: 全职
所属部门: AI广告技术部
汇报对象: AI实验室负责人
关于我们
我们是一家快速发展的科技公司,致力于通过创新的数据驱动解决方案重塑数字广告行业。我们的使命是为企业提供高性能的广告平台,实现更佳的商业效果。
职位概述
作为AI广告算法工程师,您将负责设计和实现核心广告算法,包括但不限于CTR/CVR预估、竞价策略、智能出价和受众定向等关键模块。您需要深入理解广告业务场景,持续优化基于机器学习和深度学习技术的算法性能,并与工程团队密切合作将算法部署至生产环境。
核心职责
广告核心算法研发
研究并开发创新的CTR/CVR预估模型,包括特征工程、模型架构设计和训练优化
开发基于深度学习的广告排序算法,优化eCPM等核心指标
研究并实现智能竞价策略(如bid shading、ROI优化等)
用户理解与定向
构建用户画像系统,基于表征学习开发用户嵌入表示
开发相似人群扩展算法,提升受众定向准确率
优化实时人群分群和匹配效率
算法工程化
将算法模型部署至线上系统,确保高并发场景下的稳定性和性能
开发特征平台,实现特征的高效生产和复用
构建A/B测试框架,科学评估算法效果
前沿技术探索
跟踪广告算法领域最新进展(如多任务学习、因果推断等)
探索大语言模型在广告创意生成和智能投放中的应用
研究隐私保护技术在广告场景的落地实现
任职要求
必备条件:
计算机科学、数学、统计等相关专业本科/硕士及以上学历
3年以上广告算法、推荐系统或搜索算法相关经验
扎实的机器学习基础,熟悉常用算法原理和实现
精通Python,熟悉TensorFlow/PyTorch等框架
有Spark/Flink等大数据处理工具使用经验
深入理解广告业务,熟悉DSP/SSP系统架构
优先条件:
具备大规模广告算法实战经验,熟悉DSP/SSP/RTB生态系统
在顶级会议发表过广告算法相关论文
熟悉强化学习、多任务学习等前沿技术
有特征平台、模型服务化相关工程经验
我们提供:
具有市场竞争力的薪资待遇
灵活的工作时间和远程办公选择
与行业顶尖技术团队共事的机会
持续的职业发展和技术成长空间
Full-time
