PUNE · FULLTIME
ML Engineer
Amakshar Technology
Pune · onsite · Posted 28d ago
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Undisclosed5–10 yrsfulltimePune
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Section · 01
About this role
Job Category: IT
Job Type: Full Time
Job Location: Pune Ahmedabad
Experience Level: 5+ years
Location (City, State): Ahmedabad, Pune
JD:-
Required Qualifications:
Model Monitoring & Validation
- Monitor model performance metrics (accuracy, latency, drift, bias).
- Validate prediction outputs and ensure consistency across environments.
- Support model explainability and debugging of prediction anomalies.
- Ensure data quality alignment between training and inference pipelines.
ML Pipeline Support & Monitoring
- Monitor and support ML pipelines across Azure Machine Learning, Databricks, and related services.
- Track model performance, drift, and pipeline execution failures.
- Identify issues in data ingestion, feature engineering, and model inference workflows.
- Ensure SLA adherence and operational stability in a 24 7 production environment.
Model Support & Fix Implementation
- Analyze and fix issues in Python-based ML workflows, including feature pipelines and model logic.
- Support model retraining, versioning, and deployment fixes.
- Improve model stability, performance, and monitoring coverage.
- Follow change management and deployment processes for production ML fixes.
Incident Management & Troubleshooting
- Troubleshoot failed ML pipelines, model training/inference jobs, and deployment issues.
- Analyze alerts related to model performance degradation, drift, or data inconsistencies.
- Execute resolution steps (job restarts, pipeline re-runs, endpoint fixes) and escalate when needed.
- Perform root cause analysis (RCA) for model failures, prediction anomalies, and pipeline breakdowns.
Collaboration & Continuous Improvement
- Act as escalation support (L2) and guide L1 engineers during ML-related incidents.
- Maintain runbooks for model troubleshooting, monitoring, and recovery procedures.
- Document incidents, model issues, and resolution steps.
- Identify automation opportunities in model monitoring, alerting, and retraining workflows.
Kind Note: Please apply or share your resume only if it matches the above criteria.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Section · 02
Skills
data qualityAutomationIncident ManagementData ingestionModel MonitoringAzure Machine Learningml engineerfeature engineeringChange ManagementMl PipelinesEndpointdebuggingdeploymentDatabricksPythonMicrosoft AzureMachine Learning