Description

Design and deploy AI-driven tools for real-time monitoring, anomaly detection, and root cause analysis.

This role is hybrid.

Responsibilities

• Integrate ML workflows with telemetry data sources including Splunk, Dynatrace, and Data Lakes.
• Build and fine-tune models for anomaly detection, platform restoration, and predictive maintenance.
• Automate root cause analysis workflows to reduce Mean Time to Identify (MTTI) and Mean Time to Restore (MTTR).
• Develop efficient data pipelines for ingesting and preprocessing logs, metrics, and traces.
• Deploy models in production using NVIDIA Triton, TensorFlow, or Kubernetes.

Required Skills

• 5+ years of experience in machine learning, AI model development, and production deployment.
• Strong proficiency with TensorFlow, PyTorch, and LangChain.
• Experience with NVIDIA Triton, Kubernetes, and vector databases.
• Hands-on expertise with Splunk, Dynatrace, and Data Lakes.
• Practical knowledge of Retrieval-Augmented Generation (RAG) techniques for hybrid search and agentic workflows.
• Ability to translate cross-functional AI use cases into scalable, production-ready solutions.
• Understanding of CI/CD and modern DevOps practices.

Key Skills

Education

Any Graduate