Machine Learning Engineer - Web Data Quality

At Zyte, we make the world's web data accessible to everyone.

Our technology powers data extraction at scale, helping businesses and researchers unlock the full potential of the web.We're a remote-first, multicultural team of engineers, data scientists, and innovators who believe in curiosity, collaboration, and continuous learning.

If you're passionate about building reliable AI systems and improving the quality of web data, we'd love to hear from you.About the RoleAs a Machine Learning Engineer (Web Data Quality), you'll design and implement intelligent systems that automatically detect, measure, and improve the quality of large-scale web datasets.

You'll work at the intersection of data science, AI, and distributed systems, collaborating closely with product, engineering, and data teams to make data accuracy measurable, scalable, and actionable.What You'll DoDevelop and deploy ML models for anomaly detection, schema drift, and content validationBuild and improve data quality pipelines leveraging modern data and MLOps toolsDesign and optimize embeddings and GenAI models to enhance data consistencyCollaborate with engineers to integrate AI systems into production workflowsConduct experiments, evaluate performance, and iterate for continuous improvementStay up to date on AI / ML and GenAI research to guide innovation within ZyteRequired3+ years of experience in Machine Learning / Data Science / AI EngineeringStrong Python skills and experience with ML frameworks (PyTorch, TensorFlow, scikit-learn)Experience with data validation, anomaly detection, or data quality systemsFamiliarity with data pipelines (Airflow, Spark, or similar)Understanding of model evaluation, metrics, and deployment best practicesExcellent problem-solving, communication, and collaboration skillsPreferredExperience with LangChain, LlamaIndex, or GenAI model orchestrationFamiliarity with data labeling tools and active learning approachesContributions to open-source or public ML projectsExperience working in a remote, cross-functional team environment35 days of paid time offHealth & wellness supportInclusive and supportive team environmentAttend conferences and meet with team members from across the globe.Work with cutting-edge open source technologies and tools

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