ML OPS Engineer / Tech Lead

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

Tools and Technologies:
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 '