AI ML Engineer Skills Design and develop machine learning algorithms and deep learning applications and systems for Observability data (AIOps) Hands on experience in Time series forecasting/prediction, anomaly detection ML algorithms Hands on experience in event classification and correlation ML algorithms Hands on experience on integrating with LLMs with prompt/fine-tuning/rag for effective summarization Working knowledge on implementing MCP client and server for Grafana Eco-system or similar exposure Key Skills: Programming languages: Python, R ML Frameworks: TensorFlow, PyTorch, scikit-learn Cloud platforms: Google Cloud, Azure Front-End Frameworks/Libraries: Experience with frameworks like React, Angular, or Vue.js, and libraries like jQuery. Design Tools: Proficiency in design software like Figma, Adobe XD, or Sketch. Databases: Knowledge of database technologies like MySQL, MongoDB, or PostgreSQL. Server-Side Languages: Familiarity with server-side languages like Python, Node.js, or Java. Version Control: Experience with Git and other version control systems. Testing: Knowledge of testing frameworks and methodologies. Agile Development: Experience with agile development methodologies. Communication and Collaboration: Strong communication and collaboration skills. Experience: Lead – 10 to 12 Years (Onshore and Offshore). Developers - 6 to 8 Years for Engineers