RZR Global 招聘 Machine Learning Engineer｜支持 New Grad + OPT / H1B

Base 在 San Francisco（每周三天RTO）。我们欢迎 New Grad 申请，同时对 OPT 和 H1B 非常友好。
申请链接： https://grnh.se/8jwpkt9b9us

你会做什么:

• 负责广告竞价核心模型的开发与迭代 ： CTR/CVR 预估、出价策略、预算 pacing,模型直接影响平台收入
• 把模型从实验推到生产:特征工程、训练管线、线上部署、监控与迭代,对线上效果负责到底
• 设计并跑线上实验(A/B test),用数据验证模型改进是否真的带来业务提升
• 与工程团队一起解决大规模、低延迟场景下的工程问题(毫秒级响应、日均百亿级请求)
• 与产品、算法、销售团队协作,把模糊的业务问题转化成可建模的问题

我们适合什么样的人:

• 计算机、数学、统计、EE 等相关专业, 985本科优先
• Python 扎实,熟悉主流 ML 框架(PyTorch / TensorFlow / XGBoost 等)
• 能独立处理大规模数据
• 理解常见模型背后的原理,不只是调 API;能定位线上模型效果下降的原因
• 加分项:推荐系统 / 广告排序 / 实时竞价经验,大数据工具栈(Spark、Airflow),云平台经验

为什么值得加入：

• 数据规模真实且量大,是很多公司拿不到的建模场景
• 公司支持 OPT 与 H1B
• 公司在中国有办公室，每年有机会短期回国工作
• 成长节奏快，能真正接触核心业务

介意勿申：

• 公司现在接近200人，处于快速成长阶段，工作节奏快
• 会有很多跨时区会议，一般集中在早上8-10 和晚上6-9（时间是大致范围，不会持续开会三小时）.

Machine Learning Engineer
San Francisco
Who are we?

RZR Global is an AI-driven company specializing in mobile advertising solutions designed to fuel revenue growth. We leverage AI to discover audiences in a privacy-first environment through trillions of contextual bidding signals and proprietary behavioral models. Our audience engagement platform includes creative strategy and execution. We handle 5 million mobile ad requests per second from over 10 billion devices, driving performance for both publishers and brands. We are headquartered in San Francisco, CA, with a global presence across the United States, EMEA, and APAC.

Role OverviewWe are seeking a motivated and detail-oriented Machine Learning Engineer to join our team. As an ML Engineer, you will be involved in designing and implementing machine learning models and data pipelines to enhance our programmatic demand-side platform (DSP). You will work closely with Senior MLE and other team members to drive impactful machine learning projects and contribute to innovative solutions.
Key Responsibilities

• Support the development of machine learning models to address challenges in programmatic advertising, such as predicting user responses, forecasting bid landscapes, and detecting fraud.
• Collaborate with senior data scientists and cross-functional teams (product, engineering, and analytics) to integrate models into production workflows.
• Analyze the impact of integrating new data sources and features into our models.
• Build and maintain data pipelines to process and prepare large datasets for model training and evaluation.
• Contribute ideas and assist in testing new tools, methodologies, and technologies to improve our machine learning capabilities.
• Document experiments, assumptions, and outcomes; maintain reproducibility

Required Skills / Experience

• Bachelor’s or Master's degree in Mathematics, Physics, Computer Science, or a related technical field.
• At least 1 year of professional experience in machine learning, statistical analysis, and data analysis.
• Experience with machine learning techniques such as regression, classification, and clustering.
• Proficiency in Python and SQL and familiarity with big data tools (e.g., Spark) and ML libraries (e.g., TensorFlow, PyTorch, Scikit-Learn).
• Strong grasp of probability, statistics, and data analysis principles.
• Ability to work effectively in a team environment, with good communication skills to explain complex concepts to diverse stakeholders.

Nice-to-Have

• Familiarity with system programming languages including C++ and Rust is a plus.
• Exposure to online inference systems, gRPC/REST model endpoints, or streaming features (Kafka/Flink)
• Ad-tech familiarity: auction dynamics, pacing, fraud signals, creative personalization.

谢谢。已申请。li.**@n***.edu.