(Only 24h Left) MLOps Engineer

4 weeks ago

Delhi, India Sourcebae Full time

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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