Senior Machine Learning Engineer

Job Title: Senior Machine Learning Engineer (Azure ML + Databricks + MLOps)
Experience: 5+ years in AI/ML Engineering
Employment Type: Full-Time

Job Summary:

We are looking for a Senior Machine Learning Engineer with strong expertise in Azure Machine Learning and Databricks to lead the development and deployment of scalable AI/ML solutions. You’ll work with cross-functional teams to design, build, and optimize machine learning pipelines that power critical business functions.

Key Responsibilities:

• Design, build, and deploy scalable machine learning models using Azure Machine Learning (Azure ML) and Databricks.
• Develop and maintain end-to-end ML pipelines for training, validation, and deployment.
• Collaborate with data engineers and architects to structure data pipelines on Azure Data Lake, Synapse, or Delta Lake.
• Integrate models into production environments using Azure ML endpoints, MLflow, or REST APIs.
• Monitor and maintain deployed models, ensuring performance and reliability over time.
• Use Databricks notebooks and PySpark to process and analyze large-scale datasets.
• Apply MLOps principles using tools like Azure DevOps, CI/CD pipelines, and MLflow for versioning and reproducibility.
• Ensure compliance with data governance, security, and responsible AI practices.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 5+ years of hands-on experience in machine learning or data science roles.
• Strong proficiency in Python, and experience with libraries like Scikit-learn, XGBoost, PyTorch, or TensorFlow.
• Deep experience with Azure Machine Learning services (e.g., workspaces, compute clusters, pipelines).
• Proficient in Databricks, including Spark (PySpark), notebooks, and Delta Lake.
• Strong understanding of MLOps, experiment tracking, model management, and deployment automation.
• Experience with data engineering tools (e.g., Azure Data Factory, Azure Data Lake, Azure Synapse).

Preferred Skills:

• Azure certifications (e.g., Azure AI Engineer Associate, Azure Data Scientist Associate).
• Familiarity with Kubernetes, Docker, and container-based deployments.
• Experience working with structured and unstructured data (NLP, time series, image data, etc.).
• Knowledge of cost optimization, security best practices, and scalability on Azure.
• Experience with A/B testing, monitoring model drift, and real-time inference.

Job Types: Full-time, Permanent

Benefits:

• Flexible schedule
• Paid sick time
• Paid time off
• Provident Fund

Work Location: In person