Machine Learning Engineer

📋 Description

• • Architect and own the next-generation Yahoo Mail Intelligence platform that processes petabytes of mail data daily, transforming raw messages into actionable knowledge that delights hundreds of millions of users worldwide.
• • Research, design and implement state-of-the-art algorithms for information retrieval, natural-language understanding, ranking and recommendation, pushing the boundaries of what email can do for people’s daily lives.
• • Build, enhance and continuously optimize distributed data-processing workflows in Java or Python that run on Yahoo’s massive Hadoop grid, handling terabytes per hour with rock-solid reliability and sub-second latency.
• • Leverage TensorFlow, PyTorch and other modern ML frameworks to train, evaluate and deploy classification, extraction and recommendation models that automatically surface the most relevant content, attachments, events and contacts for each user.
• • Partner with Research scientists and product managers in agile, two-week sprints to turn experimental prototypes into production-grade services that ship to 100 % of the user base with zero-downtime blue-green deployments.
• • Design clean, extensible APIs and data contracts that allow downstream teams—mobile, web, ads, search—to consume mail intelligence safely and efficiently while respecting strict privacy and security standards.
• • Instrument everything: write unit, integration and canary tests; set up real-time dashboards and alerting; and use statistical methods to detect drift, bias or degradation before users ever notice.
• • Champion code quality through peer reviews, automated style checks and continuous integration pipelines, raising the engineering bar for the entire Mail organization.
• • Mentor junior engineers and interns, sharing best practices in distributed systems, machine-learning operations (MLOps) and large-scale feature engineering.
• • Contribute to Yahoo’s open-source initiatives and publish findings at top-tier conferences, reinforcing our reputation as a technology leader in big-data AI.
• • Collaborate cross-functionally with privacy, legal and security teams to ensure every model and data pipeline complies with global regulations and Yahoo’s ethical-AI principles.
• • Stay curious—run exploratory data analyses to uncover hidden patterns in mail content, user behavior and network graphs, then translate insights into new product features that make communication simpler, faster and more delightful.