高级机器学习工程师
Senior Machine Learning Engineer
我们正在寻找一位高级机器学习工程师，负责设计、主导并扩展支持VIS.X——程序化广告平台的预测系统。您将对高影响力的机器学习项目（例如定价优化、出价预测、性能预测、交付优化）承担端到端的责任，并将复杂的业务问题转化为稳健、可生产使用的机器学习系统。这是一个具有领导潜力的高级个人贡献者职位。您将帮助塑造我们的机器学习架构、标准和长期人工智能战略，并在我们扩展数据科学能力的过程中有机会成长为团队负责人。
要求：
- 5年以上机器学习/应用机器学习相关经验，并有生产环境的系统维护经验
- 在真实环境中部署和维护机器学习系统的成功记录
- 强大的Python技能（例如，pandas、scikit-learn、PyTorch/TensorFlow）
- 扎实的统计学知识，实验设计和模型评估能力
- 处理大规模数据集和性能关键系统的工作经验
- 了解MLOps原则（模型生命周期、监控、CI/CD集成、重新训练流程）
- 强烈的问题所有者意识——能够独立构建模糊挑战的结构
- 能够将业务权衡转化为建模决策
- 有AdTech、市场或拍卖系统经验者优先
- 有高规模、实时系统工作经验者优先
职责：
- 从概念到生产阶段负责机器学习问题
- 设计、构建和部署预测模型（例如定价、出价、优化、预测）
- 为大规模数据集开发可扩展的特征工程和数据流水线
- 定义实验框架（A/B测试、离线验证、模型比较）
- 确保生产级别的MLOps：监控、重新训练、漂移检测、可靠性
- 与DevOps、产品、工程团队紧密合作，确保机器学习与业务影响一致
- 量化模型对收入、利润率和性能KPI的影响
- 参与构建我们的长期机器学习架构和最佳实践
我们提供：
- 舒适的环境、具有挑战性的任务和一个长期有趣的项目；
- 20天带薪年假；
- 使用顶级设备工作；
- 由专业会计师处理财务；
- 来自我们关怀的HR团队的帮助和支持；
最初发布于喜马拉雅山
查看英文原文
We are looking for a Senior Machine Learning Engineer to design, own, and scale predictive systems that power VIS.X - programmatic advertising platform.
You will take end-to-end responsibility for high-impact ML initiatives (e.g., pricing optimization, bid prediction, performance forecasting, delivery optimization) and translate complex business problems into robust, production-grade machine learning systems.
This is a senior individual contributor role with leadership potential. You will help shape our ML architecture, standards, and long-term AI strategy, with the opportunity to grow into a team lead role as we expand our data science capabilities.
Requirements:
- 5+ years of experience in machine learning / applied ML roles with production ownership
- Proven track record of deploying and maintaining ML systems in real-world environments
- Strong Python skills (e.g., pandas, scikit-learn, PyTorch/TensorFlow)
- Solid knowledge of statistics, experimentation design, and model evaluation
- Experience working with large-scale datasets and performance-critical systems
- Understanding of MLOps principles (model lifecycle, monitoring, CI/CD integration, retraining pipelines)
- Strong problem ownership mindset - ability to independently structure ambiguous challenges
- Ability to translate business trade-offs into modeling decisions
- Experience in AdTech, marketplaces, or auction-based systems is a plus
- Experience working in high-scale, real-time systems is a plus
Responsibilities:
- Take ownership of machine learning problems from concept to production
- Design, build, and deploy predictive models (e.g. pricing, bidding, optimization, forecasting)
- Develop scalable feature engineering and data pipelines for large-scale datasets
- Define experimentation frameworks (A/B testing, offline validation, model comparison)
- Ensure production-grade MLOps: monitoring, retraining, drift detection, reliability
- Collaborate closely with DevOps, Product, Engineering teams to align ML with business impact
- Quantify model impact on revenue, margin, and performance KPIs
- Contribute to building our long-term ML architecture and best practices
What we offer:
- Comfortable environment, challenging tasks and a long-term interesting project;
- Covered 20 days of vacation;
- Working with top notch equipment;
- Bookkeeping by a professional accountant;
- Help and support from our caring HR-team;
Originally posted on Himalayas