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Mid-senior metro ML/data role with in-demand LLM, cloud, and data skills, moderate company brand.
Core ML and data engineering skills are transferable across industries; minor telecom preference.
Explicit 5–10 years and mandatory Snowflake, ADF, Python, ML/LLM skills.
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Build, maintain, and optimize scalable cloud-native data pipelines and solutions primarily using Azure Data Factory and Snowflake.
Develop and deploy AI/ML models including Deep Learning, NLP, Large Language Models, and Generative AI applications with end-to-end ML pipelines.
Implement CI/CD pipelines for data and ML workflows; collaborate across teams to deliver enterprise data and AI solutions ensuring governance and quality.
5–10 years of professional experience in data engineering and AI/ML roles.
Strong proficiency in Python, Azure Data Factory for ETL/ELT pipelines, and Snowflake for cloud data warehousing.
Experience with AI/ML including Machine Learning, Deep Learning, NLP, LLMs, and Generative AI.
Working knowledge of Azure Cloud preferred; AWS/GCP acceptable; experience with CI/CD in data/ML workflows.
Experienced in building scalable cloud-native data and AI/ML pipeline solutions with full lifecycle ownership.
Able to translate business requirements into technical AI-driven solutions and collaborate cross-functionally with stakeholders.
Familiarity with modern DevOps practices and deployment/monitoring of AI models, preferably in enterprise settings.