Teamware Solutions is seeking a skilled professional for the Azure Machine Learning / Databricks Engineer role. This position is crucial for designing, building, and deploying scalable machine learning solutions and data pipelines within the Microsoft Azure ecosystem. You'll work with relevant technologies, ensuring smooth operations, and contributing significantly to business objectives through expert analysis, development, implementation, and troubleshooting within the Azure Machine Learning and Databricks domain.
Roles and Responsibilities :
- ML Solution Development : Design, develop, and implement end-to-end machine learning solutions, including data ingestion, feature engineering, model training, evaluation, and deployment, primarily using Azure Machine Learning and Azure Databricks .
- Data Pipeline Engineering : Build and optimize robust data pipelines for machine learning workloads, leveraging PySpark / Spark SQL within Azure Databricks for large-scale data processing and transformation.
- Azure ML Services : Work extensively with Azure Machine Learning services for model lifecycle management, including experiment tracking, model registry, and deploying models as web services or to Azure Kubernetes Service (AKS).
- Databricks Platform : Utilize Azure Databricks notebooks, clusters, and Delta Lake for collaborative data science and engineering, ensuring efficient and scalable execution of ML workloads.
- Model Optimization & Monitoring : Implement techniques for optimizing model performance and efficiency. Set up monitoring for deployed models to detect drift, bias, and performance degradation.
- Code Quality & MLOps : Write clean, maintainable, and production-ready Python / PySpark code. Contribute to MLOps practices for automating ML workflows (CI / CD for ML models).
- Troubleshooting : Perform in-depth troubleshooting, debugging, and issue resolution for ML models, data pipelines, and platform-related problems within Azure ML and Databricks environments.
- Collaboration : Work closely with data scientists, data engineers, software developers, and business stakeholders to translate machine learning concepts into deployable and impactful solutions.
Preferred Candidate Profile :
Azure ML Expertise : Strong hands-on experience with Microsoft Azure Machine Learning Studio and its associated services.Azure Databricks Proficiency : Proven experience in developing and optimizing data and ML solutions on Azure Databricks using PySpark / Spark SQL.Python Programming : Excellent proficiency in Python for data manipulation, machine learning, and scripting.Machine Learning Fundamentals : Solid understanding of core machine learning concepts, algorithms, and model evaluation metrics.Cloud Data Services : Familiarity with other Azure data services (e.g., Azure Data Lake Storage, Azure Synapse Analytics, Azure Data Factory) is a plus.SQL Knowledge : Good proficiency in SQL for data querying and manipulation.Problem-Solving : Exceptional analytical and problem-solving skills with a methodical approach to complex data science and engineering challenges.Communication : Strong verbal and written communication skills to articulate technical solutions and collaborate effectively within a team.Education : Bachelor's degree in Computer Science, Data Science, Statistics, or a related technical field. Azure certifications related to Data Science or AI are a strong plus.Skills Required
Azure ML, Pyspark, Python, Sql