About
Architect and lead development of advanced machine learning models and data validation systems Design and optimize ML infrastructure, including scalable distributed pipelines and automated validation frameworks Drive data quality standards and lead cross-functional initiatives from requirements definition to production deployment
Required Qualifications
7+ years of experience in Machine Learning Engineering, Data Engineering, or a similar technical role Expert-level proficiency in Python, ML frameworks, and distributed data processing (Spark, Hive) Deep understanding of data quality methodologies and validation frameworks Strong experience designing and scaling ML infrastructure and production-grade deployment workflows Hands-on experience with cloud-native architectures, ideally on AWS
Languages
- English
Notice for Users
This job comes from a TieTalent partner platform. Click "Apply Now" to submit your application directly on their site.