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Job Description
Structured overview of role & requirementsAbout This Role
Implement machine learning models into production in collaboration with Data Science teams.
Design, deliver, and manage industrialized processing pipelines and ML/AI operational frameworks.
Define and apply best practices for ML model lifecycle, MLOps/LLMOps, and present solutions to internal and external clients.
Minimum Requirements
5+ years Data engineering experience; last 3 years building data processing systems.
3+ years production-ready ML code development experience, 5+ years Python production code development.
Experience with MLOps/LLMOps tools such as AzureML, AzureAI, or GCP VertexAI and Databricks.
Practical experience in Spark/PySpark, Hive on Big Data Platforms, and working knowledge of cloud (preferably Azure or GCP).
Ideal Candidate Profile
Experienced in production deployment and operational management of ML models and pipelines in cloud environments.
Strong background in building ML-based production recommendation systems and data processing pipelines.
Familiar with ML/AI concepts, model efficiency metrics, and implementing scalable automation solutions for ML lifecycle management.