Description

Key Skills: Databricks, SQL, Pytorch, Python, Tensorflow, SSRS

Roles and Responsibilities:

• Convert data science Proof-of-Concept solutions into production-grade, automated pipelines hosted in Databricks (Cloud).
• Implement CI/CD, model deployment automation, and MLOps best practices.
• Build scalable data and model pipelines, ensuring reliability and observability.
• Monitor model and pipeline performance; implement alerting and issue remediation.
• Maintain and enhance existing production tools and ML workloads.
• Ensure alignment with EM Enterprise AI standards, architecture guidelines, and security requirements.
• Collaborate with Data Scientists and platform teams to ensure seamless migration and sustainment.
• Implement CI/CD pipelines for data workflows and analytics applications in AI/ML frameworks (PyTorch, TensorFlow, Scikit-learn) and build end-to-end ML pipelines.

Skills Required:

• Strong proficiency in PyTorch and TensorFlow for model implementation
• Expertise in Python programming and SQL for data manipulation and pipelines
• Experience with Databricks for scalable production ML pipelines
• Knowledge of classical ML techniques: regression, classification, and time series analysis
• Implementing CI/CD pipelines and MLOps best practices
• Monitoring, logging, and performance optimization of ML models and workflows
• Familiarity with production tools and maintaining ML workloads
• Understanding of enterprise AI architecture standards and security compliance
• Collaboration skills to work effectively with Data Scientists and platform teams
• Knowledge of SSRS for reporting (nice-to-have)

Education: Any Graduation

Key Skills

Education

Any Graduate