Scalable Machine Learning Engineer

13 hours ago

tiruppur, India beBeeMLOps Full time

Machine Learning Operations ProfessionalWe are seeking an experienced Databricks professional to design, build, and manage scalable machine learning operations on the Databricks Lakehouse Platform.Main Responsibilities:1. Develop Scalable MLOps Pipelines:Create automated ML workflows, operationalize models, ensure reproducible pipelines, and implement governance and monitoring across the ML lifecycle.Bull automated ML pipelines for training, validation, deployment, and batch/real-time inference using Databricks Workflows, Jobs, Repos, and Delta Live Tables.Implement distributed training and inference pipelines using MLflow + PySpark.2. Model Lifecycle Management:Manage model versioning and promotion across dev → staging → production using MLflow Model Registry.Create reproducible workflows for model packaging, deployment, and rollback.3. CI/CD Integration:Build and integrate ML pipelines with CI/CD using Azure DevOps, GitHub Actions, or Jenkins.Automate testing, validation, and deployment for ML artifacts, notebooks, and infrastructure.4. Feature Engineering & Data Pipelines:Collaborate with data engineering teams to build optimized Delta Lake pipelines (Bronze/Silver/Gold architecture).Implement feature engineering workflows and support feature reuse at scale.5. Monitoring & Governance:Set up model monitoring for performance, drift, data quality, and lineage.Use Databricks-native tools, MLflow metrics, and cloud monitoring services.Ensure compliance through logging, auditing, permissions, and environment governance.6. Cross-Functional Collaboration:Work closely with data scientists, data engineers, cloud teams, and product teams.Document workflows, best practices, and MLOps reusable components.What We Offer:A dynamic work environment with a team of experts in machine learning operations.Opportunities for growth and professional development in a rapidly evolving field.

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