Description

You will design and implement machine learning algorithms and deep learning applications focused on observability data and AIOps.

This role is on-site.

Responsibilities

• Architect advanced algorithms for time series forecasting, anomaly detection, event classification, and correlation.
• Develop deep learning systems for observability data.
• Integrate large language models (LLMs) and generative AI using prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• Implement MCP client and server within the Grafana ecosystem or similar platforms.
• Lead and mentor onshore and offshore engineering teams.

Required Skills

• 5+ years of experience in machine learning architecture.
• Proficiency in Python and R.
• Extensive experience with TensorFlow, PyTorch, and scikit-learn.
• Proven experience with GenAI, including prompt engineering, fine-tuning, and RAG.
• Working knowledge of Google Cloud and Azure.
• Proficiency in MySQL, MongoDB, and PostgreSQL.
• Familiarity with Node.js and Java.
• Experience with Git and version control systems.
• Proficiency in Figma, Adobe XD, or Sketch.

Preferred Skills

• Experience with agile development methodologies and testing frameworks.

Key Skills

Education

Any Gradute