Ml Engineer

3 weeks ago


Bengaluru, India Wipro Full time

Role & responsibilities

ML Engineer

Role Summary
Implements and operationalizes machine learning models, managing the end-to-end ML lifecycle including training, deployment, and monitoring.

Detailed Responsibilities

  • Package and deploy ML models using Azure ML pipelines.
  • Automate retraining and versioning workflows.
  • Build and maintain model scoring APIs and batch inference jobs.
  • Monitor performance and drift in deployed models.
  • Implement CI/CD for ML (MLOps).
  • Optimize resource utilization and performance of ML workloads.

Key Skills and Technologies

  • Azure ML, MLflow
  • Python (ML frameworks)
  • AKS (Azure Kubernetes Service) for model hosting
  • CI/CD for ML workflows
  • Model monitoring and alerting

Experience and Qualifications

  • 5+ years in ML engineering or MLOps.
  • Experience deploying models to production on Azure.

Key Deliverables and Outcomes

  • Automated training and deployment pipelines.
  • Production inference APIs with monitoring dashboards.
  • Model rollback and versioning strategies.

KPIs / Measures of Success

  • Deployment success rate.
  • Model latency and performance.
  • Drift detection and remediation timelines.

Reporting and Collaboration

  • Reports to AI Architect.
  • Works with Data Scientists, Backend Developers, and DevOps teams.

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