Develop and maintain Python-based applications and automation scripts.
Design, build, and deploy AI/ML models for performance analytics and anomaly detection.
Implement and manage APM tools (e.g., Dynatrace, AppDynamics, New Relic, Splunk APM).
Analyze system performance data and identify bottlenecks, trends, and root causes.
Integrate monitoring data with ML pipelines for predictive performance and alerting.
Collaborate with DevOps, SRE, and engineering teams to improve system reliability.
Create dashboards, reports, and documentation for performance insights.
Requirements
Strong Python programming experience (Pandas, NumPy, Flask/FastAPI).
Experience in AI/ML (scikit-learn, TensorFlow, PyTorch, ML pipelines).
Hands-on experience with APM tools and monitoring frameworks.
Knowledge of data analysis, anomaly detection, and predictive modeling.
Understanding of cloud platforms (AWS/GCP/Azure) and DevOps tools (Docker, Kubernetes).
SQL/NoSQL database knowledge.
Strong Python programming experience (Pandas, NumPy, Flask/FastAPI).
Experience in AI/ML (scikit-learn, TensorFlow, PyTorch, ML pipelines).
Hands-on experience with APM tools and monitoring frameworks.
Knowledge of data analysis, anomaly detection, and predictive modeling.
Understanding of cloud platforms (AWS/GCP/Azure) and DevOps tools (Docker, Kubernetes).
SQL/NoSQL database knowledge.
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