Machine Learning Engineer
Há 2 dias
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 Role As 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 Do Develop and deploy ML models for anomaly detection, schema drift, and content validation Build and improve data quality pipelines leveraging modern data and MLOps tools Design and optimize embeddings and GenAI models to enhance data consistency Collaborate with engineers to integrate AI systems into production workflows Conduct experiments, evaluate performance, and iterate for continuous improvement Stay up to date on AI/ML and GenAI research to guide innovation within Zyte Required 3+ years of experience in Machine Learning / Data Science / AI Engineering Strong Python skills and experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) Experience with data validation, anomaly detection, or data quality systems Familiarity with data pipelines (Airflow, Spark, or similar) Understanding of model evaluation, metrics, and deployment best practices Excellent problem-solving, communication, and collaboration skills Preferred Experience with LangChain, LlamaIndex, or GenAI model orchestration Familiarity with data labeling tools and active learning approaches Contributions to open-source or public ML projects Experience working in a remote, cross-functional team environment 35 days of paid time off Health & wellness support Inclusive and supportive team environment Attend conferences and meet with team members from across the globe. Work with cutting-edge open source technologies and tools #J-18808-Ljbffr
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