Machine Learning Engineer - Microsoft Fabric

Description :

Job Summary :

We are seeking an experienced ML Engineer with strong hands-on expertise in Microsoft Fabric to design, build, and deploy end-to-end machine learning workflows for enterprise clients.

The role involves developing scalable ML solutions using Fabric Data Science, Azure Machine Learning, and Spark-based frameworks, while ensuring production-grade deployment, monitoring, and integration with analytics platforms.

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 :

Candidates should have 68 of the following skills :

- 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