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 Khushboo@Sourcebae.com or share it via WhatsApp at 8827565832

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