6–8 years of industry experience in AI/ML model development and data analysis.
Strong programming skills in Python (Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch).
Solid understanding of machine learning algorithms, model evaluation techniques, and data preprocessing.
Experience working with APIs, REST services, or integrating ML components into applications.
Familiarity with version control (Git) and collaborative tools (Jira, Confluence, etc.).
Exposure to Agentic AI concepts – experience with autonomous agents, goal-oriented systems, or multi-agent frameworks (e.g., LangChain, Auto-GPT, ReAct pattern).
Ability to communicate complex technical ideas clearly to non-ML stakeholders
Exposure to or interest in test automation frameworks like Selenium, Cypress, or Playwright.
Knowledge of software testing concepts and SDLC/STLC processes.
Experience with natural language processing (NLP) for analyzing logs or test case metadata.
Hands-on experience with cloud platforms (AWS, GCP, Azure) for model deployment.
Previous work involving self-healing tests or intelligent failure analysis is a big plus.