高级机器学习工程师 - 排名方向
Senior Machine Learning Engineer - Ranking
为数字媒体中的性能市场提供支持
QuinStreet 是在推动去中心化在线市场方面的先驱，这些市场将搜索者和“研究与比较”消费者与品牌相匹配。我们在国内最大的媒体网络之一中运营这些虚拟和私有品牌的市场。
我们行业领先的细分技术和由人工智能驱动的匹配技术帮助消费者更快找到更好的解决方案，同时帮助品牌精准定位并触达有购买意向的客户，并且只为其性能结果付费。
我们的以活动结果为导向的匹配决策引擎和优化算法建立在超过20年和数十亿美元的在线媒体经验之上。
我们相信：
- 数字媒体的直接可衡量性。
- 性能营销。（我们是这一领域的先驱。）
- 技术的优势。
我们将所有这些整合在一起，为消费者和品牌在世界上最大的渠道中带来真正出色的结果。
职位类别
加入我们，共同塑造用户如何发现和与我们的市场进行互动。你将推进排序、优先级和个性化的算法。排名是一个核心组件，它帮助用户发现广告，平衡用户满意度、业务目标和系统健康状况。
职责
- 通过严格的测量和实验设计和改进排名系统；将广泛的目标转化为清晰的指标并实现持续的、经过验证的提升。
- 推进评估实践（清洁测试设计、离线与在线对齐），帮助团队做出基于证据的决策。
- 构建高价值的信号和特征，使用可靠的离线/在线管道和强大的监控机制。融入内容理解信号，如文本/图像/元数据。
- 做出具有不确定性的决策；处理漂移和校准，使模型在长时间内保持稳定和可信。
- 与工程、产品、业务和分析团队合作，端到端地交付稳健的解决方案。
要求
- 计算机科学、统计学或相关领域的高级学位（硕士/博士），具有3年以上博士后经验或5年以上行业经验。
- 在应用机器学习、统计学和优化方面有扎实的基础，并在排序/推荐方面有显著影响。
- 精通 Python 和扎实的软件工程实践（测试、CI/CD）。
- 具有处理大规模数据集、分布式系统和延迟敏感的生产机器学习的经验。
- 清晰的沟通能力，跨职能协作能力，以及主人翁精神。
查看英文原文
Powering Performance Marketplaces in Digital Media
QuinStreet is a pioneer in powering decentralized online marketplaces that match searchers and “research and compare” consumers with brands. We run these virtual- and private-label marketplaces in one of the nation’s largest media networks.
Our industry leading segmentation and AI-driven matching technologies help consumers find better solutions and brands faster. They allow brands to target and reach in-market customer prospects with pinpoint segment-by-segment accuracy, and to pay only for performance results.
Our campaign-results-driven matching decision engines and optimization algorithms are built from over 20 years and billions of dollars of online media experience.
We believe in:
- The direct measurability of digital media.
- Performance marketing. (We pioneered it.)
- The advantages of technology.
We bring all this together to deliver truly great results for consumers and brands in the world’s biggest channel.
Job Category
Join us to shape how users discover and interact with our marketplace. You’ll advance algorithms for ordering, prioritization, and personalization. Ranking is a core component which helps users discover ads, balance user satisfaction, business goals, and system health.
Responsibilities
- Design and improve ranking systems through rigorous measurement and experimentation; translate broad goals into clear metrics and deliver steady, validated gains.
- Advance evaluation practices (clean test design, offline & online alignment) and help teams make evidence-based decisions.
- Build high-value signals and features with reliable offline/online pipelines and robust monitoring. Incorporate content understanding signals such as text/image/metadata.
- Make uncertainty-aware decisions; handle drift and calibration so models remain stable and trustworthy over time.
- Partner with Engineering, Product, Business and Analytics to ship resilient solutions end-to-end.
Requirements
- Advanced degree (MS/PhD) in CS, Statistics, or related field, with 3+ years post-PhD or 5+ years industry experience.
- Strong foundations in applied ML, statistics, and optimization with demonstrated impact in ranking/recommendations.
- Proficiency in Python and solid software engineering practices (testing, CI/CD).
- Experience working with large-scale datasets, distributed systems, and latency-sensitive production ML.
- Clear communication, cross-functional collaboration, and an ownership mindset.
Preferred
- Demonstrated success in delivering production-grade ranking systems with measurable business impact.
- Track record building feature/signals pipelines, feature stores, and observability for ML systems.
- Depth in experimentation and metrics design, including large-scale A/B testing and variance reduction.
- Familiarity with monitoring, calibration, concept drift detection, and adaptive or online learning.
- Proficiency in SQL is desired.
- Knowledge about Linear Algebra, Combinatorial optimization is desired.
- Proficiency in scalable software design and development.
- Exposure to multimodal signals (text/image/metadata) is a plus, not required.
The expected salary range for this position is $140,000 USD to $170,000 USD annually. This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices. The salary may be adjusted based on applicant's geographic location. The position is also eligible to receive performance bonus or commission and equity in the form of restricted stock units. This position is eligible to participate in the Company’s standard employee benefits programs, which currently include health care benefits; (2) retirement benefits; (3) the amount of paid days off (paid sick leave, parental leave, paid time off, or vacation benefits); (4) any other tax-reportable benefits.
QuinStreet is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, national origin, pregnancy status, sex, age, marital status, disability, sexual orientation, gender identity or any other characteristics protected by law.
Please see QuinStreet’s Employee Privacy Notice here.
Originally posted on Himalayas