Professional Summary

• Experienced AI/ML Validator with 4 years of expertise in validating model outputs and ensuring production reliability
• Proficient in implementing A/B testing and canary deployment procedures for ML models
• Skilled in monitoring model performance in production and setting up automated alerts for drift detection
• Knowledgeable in defining success metrics, thresholds, and KPIs for ML model evaluation
• Experienced in gradual rollout strategies and rollback mechanisms for safe model deployment
• Familiar with data science tools, statistical analysis, and model interpretability techniques
• Collaborative professional working with ML engineers and data scientists on model validation
• Strong analytical skills for identifying model biases and performance degradation

Work Experience

AI/ML Validator

[Company name] · [Start date – End date]

4 years of experience as an AI/ML Validator at a leading AI company in Bangalore. Specialized in model validation, A/B testing, and production monitoring for machine learning applications.

Responsibilities

• Implement A/B testing and canary deployment procedures for ML models
• Monitor model performance in production and set up alerts for drift
• Define success metrics, thresholds, and KPIs for model evaluation
• Collaborate with ML teams on model validation and deployment strategies
• Analyze model biases and ensure fairness in production
• Set up monitoring dashboards and automated reporting
• Provide recommendations for model improvements and optimizations
• Ensure compliance with ethical AI guidelines and standards
• Validate LLM-powered AI systems: hallucination detection, RAG pipeline accuracy (RAGAS), agentic workflow reliability, prompt injection security testing, and AI safety/alignment assessment
• Monitor production LLM systems with LangSmith tracing and implement continuous evaluation pipelines for deployed AI assistants

Project Experience