Must-Have Skills:
- Experience testing AI/ML solutions including Generative AI, Conversational AI, and Predictive models
- Strong understanding of ML lifecycle data prep, training, validation, and tuning
- Knowledge of ML algorithms including regression, classification, clustering, neural networks, and transformers
- Proficiency in Python, pandas, NumPy, and scikit-learn
- Experience validating model outputs, data quality, and evaluation metrics
- Exposure to FastAPI/Flask-based AI services and AWS SageMaker deployments
- Understanding of production ML lifecycle, deployment validation, and monitoring
Desirable Skills:
- Testing Generative AI prompts, hallucinations, and response quality
- Responsible AI, fairness, bias, and safety validation
- MLOps pipelines and CI/CD validation for ML systems
- Performance and scalability testing for AI services
- Adversarial and edge-case AI testing
Qualification: BE/BTech in Computer Science or relevant streams
