MLOps Engineer

Job Title : MLOps Engineer

Location : Ghansoli, Navi Mumbai

Experience : 4–8 Years

Notice Period : Immediate joiners preferred or within 15 days

Job Description :

We are seeking a skilled MLOps Engineer with hands-on experience in Azure, Databricks, and DevOps to design, automate, and maintain ML pipelines and production-ready models. The ideal candidate will have strong experience in ML pipeline automation, cloud infrastructure, model governance, and monitoring to ensure scalable, robust, and compliant ML solutions.

Key Responsibilities :

ML Pipeline Design & Automation

Build and maintain CI / CD & CT (Continuous Training) pipelines for ML models using Azure DevOps and Databricks Asset Bundles .

Automate data preprocessing, training, inference, and retraining workflows for large-scale ML deployments.

Implement incremental backfills and rolling window retraining for time-series forecasting.

Deployment & Infrastructure

Design job clusters and compute policies in Databricks for optimal cost-performance trade-offs.

Implement multi-environment deployment flows (Dev → QA → Prod) with approvals and rollback strategies.

Deploy ML models to production with monitoring hooks for performance and drift detection.

Data & Model Governance

Integrate with Unity Catalog for secure, compliant data and model storage.

Set up model versioning, lineage tracking, and reproducibility using MLflow .

Establish dataset and feature versioning using tools like Databricks Feature Store .

Monitoring & Observability

Implement structured logging for model metrics, system performance, and data quality checks.

Integrate monitoring tools (e.g., Azure Application Insights ) for alerting and dashboards.

Develop automated retraining triggers based on performance degradation.

Mandatory Skills :

Cloud : Azure (mandatory) – Cloud & DevOps expertise.

ML Pipeline Automation : Azure DevOps / GitHub Actions.

Databricks : Asset Bundles, Unity Catalog, Feature Store.

Model Registry & Experiment Tracking : MLflow (or Weights & Biases).

Programming & Tools : Python (pandas, PySpark, scikit-learn, Prophet, ML / DL frameworks), Bash / PowerShell scripting, Git.

Testing & Quality : Data validation, schema enforcement, model testing, CI / CD quality gates.

Strong communication and stakeholder management skills.

Good-to-Have Skills :

Experience with time-series forecasting at scale (Prophet, Sarima, XGBoost).

Retail demand forecasting or energy sector analytics.

Feature engineering at scale with distributed systems.

If Intrested. Please submit your CV to or share it via WhatsApp at

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