美图集团
用户画像算法工程师（厦门）
岗位职责
负责美图全域用户画像体系建设，优化数据处理与标签生产流程，保障画像数据质量，支撑影像产品、AIGC、个性化推荐业务；
构建迭代用户兴趣、意图、分层等画像模型，基于多源行为数据挖掘用户偏好，产出标签与用户向量；
结合大模型、Agent技术探索新一代用户理解方案，赋能AI Agent个性化能力；画像能力对接产品运营策略、搜索推荐链路等，参与A/B实验，驱动业务指标提升；
对接产品、运营，输出数据洞察，迭代算法方案，持续优化系统性能
任职要求
计算机/统计/AI相关硕士及以上，3年+算法开发经验，具备扎实的数学和数据挖掘功底，熟悉特征工程、用户建模，有大规模用户画像落地经验的优先；
掌握Python/Java/Scala至少一门语言，至少掌握PyTorch/LightGBM/XGBoost一个机器学习工具，熟悉Hive、Spark、Flink等大数据组件的优先；
了解大模型、Agent相关技术，能够落地大模型增强用户理解相关方案；
对数据敏感，具备业务理解能力，善于通过实验验证算法效果，良好沟通与团队协作。 优先
有搜索推荐算法实战经验优先
有工具/影像/AIGC产品画像经验优先 Algorithm Engineer – User Profiling · Xiamen At Meitu, user profiling is not a support layer — it is the foundation underneath products like BeautyPlus, AirBrush, and our AIGC creation flows. We are building a global user understanding system that turns multimodal behavior into reliable preference, interest, and intent signals. You will work across the full loop: data pipeline, model design, offline evaluation, online A/B testing, and iteration. This role sits at the intersection of classical user modeling and newer LLM/Agent-based understanding, with real room to explore and ship. Your Core Work: · Own the global user profiling data pipeline and tag production process, including quality standards that support imaging products, AIGC features, and personalized recommendation;
Design and iterate user interest, intent, and segmentation models, turning multi-source behavioral data into user tags and embeddings;
Explore LLM and Agent-based approaches for next-generation user understanding, and connect those signals to AI Agent personalization;
Partner with product, operations, search, and recommendation teams to run A/B experiments and translate profiling output into measurable business impact;
Use data insights to refine algorithm design and improve system performance end to end. What We Hope You Have: · MS or higher in Computer Science, Statistics, AI, or a related field, with 3+ years of algorithm development experience;
Solid grounding in mathematics and data mining, with hands-on experience in feature engineering and user modeling;
Proficiency in at least one of Python, Java, or Scala, and practical experience with at least one ML framework such as PyTorch, LightGBM, or XGBoost;
Working knowledge of LLM and Agent technologies, with the ability to apply them to user understanding problems;
Strong data intuition and business sense, with experience validating algorithm changes through experiments and collaborating across teams. Nice to Have: · Production experience building large-scale user profiling systems;
Familiarity with big data components such as Hive, Spark, or Flink;
Hands-on experience with search or recommendation algorithms;
Background working on profiling for utility, imaging, or AIGC products.
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