Job Title: MLFlow Engineer (MLFlow 3.x)

Hybrid : Pune / Bangalore / Gurugram/ Hyderabad /Cochi/Noida/Chennai

Employment Type: Full-time

About the Role

We are seeking a skilled MLFlow 3 Engineer to join our Data & AI Engineering team. The ideal candidate will have hands-on experience in managing the end-to-end lifecycle of machine learning models using MLFlow 3.x, along with expertise in Python, Databricks, PySpark, and Azure. The role is a cusp between ML Engineering and MLOPs. You will work closely with data scientists, ML engineers, and DevOps teams to operationalize ML workflows, ensuring scalability, reliability, and compliance.

Key Responsibilities

• Design, implement, and maintain MLFlow 3.x tracking, model registry, and deployment pipelines.
• Integrate MLFlow with Databricks, Azure ML, and CI/CD pipelines for automated model deployment.
• Develop and optimize PySpark data processing pipelines for model training and evaluation.
• Manage and monitor model performance, retraining, and version control.
• Optimize infrastructure for scalability, cost efficiency, and performance within Azure environments.
• Create documentation and reusable templates for ML model management and deployment.
• Ensure adherence to data governance, compliance, and security best practices.

Required Skills & Qualifications

• 3–6 years of experience in Machine Learning Engineering, MLOps, or related roles.
• Strong hands-on experience with MLFlow 3.x (tracking, registry, model serving).
• Proficiency in Python programming for building and deploying ML models.
• Experience with Databricks for ML lifecycle management and data engineering.
• Solid knowledge of PySpark for distributed data processing.
• Working experience with Microsoft Azure (Azure Databricks, Azure ML, Azure Data Lake, etc.).
• Experience integrating ML pipelines with CI/CD tools (e.g., Azure DevOps, GitHub Actions).
• Understanding of containerization and orchestration (Docker, Kubernetes).
• Strong problem-solving skills and ability to work in cross-functional teams.

Preferred Qualifications

• Experience in MLOps automation and infrastructure as code (Terraform/ARM templates).
• Familiarity with model monitoring and drift detection frameworks.
• Knowledge of API-based model serving using MLFlow or Databricks endpoints.
• Azure certifications (e.g., Azure Data Engineer Associate, Azure AI Engineer Associate) are a plus.