Senior MLOps Engineer - Databricks

Role: Senior MLOps Engineer - Databricks

Location: Hyderabad, India

Work Mode: 100 percent Onsite

Working Hours: 9:00 AM to 6:00 PM

Working Days: Monday to Friday

About the Role

We are looking for a highly experienced Senior MLOps Engineer specializing in the Databricks platform to design, automate, deploy, monitor, and govern enterprise machine learning solutions.

The ideal candidate should have strong hands-on experience with Databricks, MLflow, CI CD, cloud infrastructure, model deployment, and production machine learning systems.

The candidate should be able to take ownership of the complete machine learning lifecycle from experimentation through production.

Key Responsibilities

• Design and implement enterprise-grade MLOps architecture on Databricks
• Build automated pipelines for model training, model validation, model evaluation, model registration, deployment, monitoring, and retraining
• Implement ML experiment tracking and lifecycle management using MLflow
• Manage production models using MLflow Model Registry and Unity Catalog
• Deploy and operate machine learning models using Databricks Model Serving
• Build ML workflow orchestration using Databricks jobs and workflows
• Implement CI CD processes for ML code, models, data pipelines, and Databricks resources
• Use Databricks Asset Bundles or Declarative Automation Bundles for deployment automation
• Use Infrastructure as Code practices to manage development, QA, and production environments
• Establish standards for model versioning, reproducibility, approvals, rollback, and release management
• Build monitoring frameworks for model performance, data quality, data drift, model drift, pipeline health, and infrastructure performance
• Implement security, access control, lineage, and governance using Unity Catalog
• Partner with Data Scientists to productionize notebooks and experimental machine learning code
• Work closely with Data Engineering and Platform Engineering teams to build reliable production ML infrastructure
• Optimize Databricks compute and ML workloads for performance, scalability, reliability, and cost
• Troubleshoot complex production ML pipeline and model serving issues
• Define MLOps standards, reusable frameworks, templates, and engineering best practices
• Mentor junior and mid-level engineers
• Provide technical leadership on MLOps initiatives

Required Skills

• 7 to 10 or more years of overall Software Engineering, Data Engineering, DevOps, Machine Learning Engineering, or related experience
• At least 4 years of strong hands-on MLOps experience preferred
• Strong production experience with Databricks
• Strong experience with MLflow
• Strong Python programming skills
• Experience with PySpark and Apache Spark
• Strong SQL skills
• Experience with Unity Catalog
• Experience with Delta Lake
• Experience with Model Registry
• Experience with Databricks Model Serving
• Strong understanding of the complete machine learning lifecycle
• Experience productionizing machine learning models
• Experience with machine learning frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow
• Strong experience implementing CI CD for machine learning workloads
• Experience with Git
• Experience with CI CD platforms such as Azure DevOps, GitHub Actions, GitLab CI, or Jenkins
• Strong cloud experience with Azure, AWS, or GCP
• Experience with Terraform or similar Infrastructure as Code tools
• Strong understanding of monitoring, observability, logging, alerting, and production support
• Experience working with REST APIs and model serving architectures
• Strong understanding of security, governance, IAM, secrets management, and production access controls
• Excellent troubleshooting and system design skills

Preferred Skills

• Databricks certification
• Advanced experience with Databricks Asset Bundles or Declarative Automation Bundles
• Experience with Databricks Feature Engineering or Feature Store
• Experience developing reusable MLOps frameworks
• Experience with Docker and Kubernetes
• Experience with enterprise model monitoring and observability tools
• Experience supporting Generative AI and LLM workloads on Databricks
• Experience with automated model evaluation and validation
• Knowledge of responsible AI and model governance
• Previous experience mentoring engineers or working as a technical lead

Required Qualifications

Bachelor's or Master's degree in Computer Science, Engineering, Machine Learning, Data Science, Information Technology, or a related technical discipline.

Work Requirements

This is a fully onsite position in Hyderabad. Candidates must be available to work from the office Monday through Friday from 9:00 AM to 6:00 PM.