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ML Operations Engineer (MLOps)
Scouterly
Job Description
Job Title: ML Operations Engineer (MLOps)
Company: Scouterly
Location: Pune, India
Experience: 4–7 Years
Level: P3 / P4
Domain: Traditional Machine Learning Models (Non-LLM / Non-GenAI)
Employment Type: Full Time
About the Role
We are actively hiring an ML Operations Engineer to join our AI & Agent Operations Team. If you have experience in deploying, monitoring, and maintaining machine learning models in production environments, we would love to hear from you.
Key Responsibilities
- Deploy and retrain machine learning models in production.
- Monitor data, feature, and concept drift.
- Perform model validation using champion-challenger testing and backtesting.
- Manage model lineage, versioning, and governance records.
- Execute model rollback procedures when required.
- Generate model performance and operational reports.
- Work closely with Data Engineering teams on data quality improvements.
- Support use cases such as churn prediction, fraud detection, and forecasting.
Required Skills
- Python
- MLOps / DevOps / ML Engineering
- CI/CD Pipelines
- Model Deployment & Monitoring
- Drift Detection & Performance Reporting
- Data Processing & Analytics
- Model Registry & Lineage Management
Preferred Skills
- Telecom Domain Experience
- Cloud ML Services (AWS/Azure/GCP)
- ML or Cloud Certifications
- Experience with Churn, Fraud, or Forecasting Models
Qualifications
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.