Machine Learning Operations (MLOps) Engineer
On-siteKotwalucheruvu Tanda, State of Telangāna, Republic of India
Job Summary
Design, build, and maintain CI/CD pipelines for machine learning workflows covering model training, validation, packaging, and deployment. Implement and manage model serving infrastructure for batch, real-time, and streaming inference while establishing observability frameworks to monitor data drift, performance degradation, latency, and bias. Build feature pipelines and stores ensuring data lineage, manage experiment tracking and artifact versioning, and automate testing frameworks including unit and integration tests. Collaborate on security controls, secrets management, and audit logging; optimize infrastructure for autoscaling, GPU utilization, and cost efficiency. Develop operational runbooks, SLAs, and incident response processes. Contribute to reference architectures and reusable engineering templates for ML platforms.
Required Qualifications
- 6-9 Years
- Machine Learning Operations (MLOps) and ML platform engineering
- CI/CD pipelines for ML workflows
- ML model deployment patterns (batch, real-time, streaming)
- Model observability and monitoring
- Feature pipelines and feature stores
- Experiment tracking, model registry, and artifact management
- Model testing frameworks (unit and integration testing)
- ML governance, security, and compliance practices
- Autoscaling infrastructure, GPU utilization, and workload scheduling
- Operational dashboards and incident management processes
- ML reference architectures and reusable engineering templates
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