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
(ref:hirist.tech)
