Machine Learning Engineer - Microsoft Fabric

Description

Job Summary :

Key Responsibilities

• Design, develop, and deploy end-to-end ML pipelines using Microsoft Fabric Data Science experience
• Build, train, evaluate, and operationalize machine learning models for enterprise use cases
• Track experiments, manage model versions, and enable reproducibility using MLflow
• Implement distributed machine learning workflows using SynapseML on Spark
• Develop and manage Azure Machine Learning pipelines, online endpoints, and batch inference jobs
• Enable in-database scoring using the PREDICT function in Fabric Warehouse
• Integrate ML outputs with analytics and reporting using Semantic Link and Power BI
• Collaborate with data engineers, analytics teams, and business stakeholders to translate requirements into ML solutions
• Ensure best practices for model governance, performance, scalability, and security
• Create clear technical documentation and actively participate in client-facing discussions
  

Technical Skills Required

• Microsoft Fabric Data Science experience (Notebooks, experiments, models)
• MLflow for experiment tracking and model registry
• SynapseML for distributed machine learning on Spark
• Azure Machine Learning (pipelines, managed endpoints, AutoML)
• PREDICT function for in-database inference in Fabric Warehouse
• ML frameworks such as scikit-learn, XGBoost, LightGBM within Fabric notebooks
• Deep learning using PyTorch and/or TensorFlow on Fabric Spark clusters
• Semantic Link for integration between Power BI and machine learning workloads
  

Experience & Qualifications

• 3+ years of experience in Machine Learning Engineering
• At least 1 year of hands-on experience with Azure Machine Learning and/or Microsoft Fabric
• Delivered 2 or more production-grade ML models with MLflow-based tracking and deployment
• Strong understanding of ML lifecycle management, model monitoring, and optimization
• Excellent communication skills for client interaction and technical documentation
  

Nice To Have

• Experience working in enterprise or consulting environments
• Exposure to MLOps best practices on Azure
• Familiarity with data warehousing and analytics workflows in Microsoft Fabric