AI Model Validator

Devitechs; United (PA); On-site; USD 90,000 - 130,000; Full time

Job summary

Devitechs is seeking a skilled AI validation engineer to ensure performance and fairness across deployed models. You will validate AI and ML systems, design tests, and work with data scientists to refine models using validation feedback.

The role emphasizes automated testing frameworks for continuous validation and ongoing improvement of model reliability. The ideal candidate brings strong experience in model validation, proficiency in Python/R/SQL, and familiarity with TensorFlow, PyTorch, and

Qualifications

• Experience validating AI models and ML systems.
• Proficiency in Python, R, or SQL.
• Familiarity with TensorFlow, PyTorch, scikit-learn.
• Knowledge of statistical techniques and model evaluation metrics.

Responsibilities

• Validate AI and ML models to ensure performance and accuracy.
• Design and execute test cases to identify issues and biases in AI models.
• Collaborate with data scientists and engineers to refine models based on validation feedback.
• Develop automated testing frameworks for continuous validation of deployed models.
• Provide recommendations for improving model reliability, robustness, and fairness.

Skills

AI validation

Python/SQL/R

ML frameworks

Statistics & metrics

Education

Bachelor’s or Master’s in CS/Data Science

Job description

Responsibilities

• Validate AI and machine learning models to ensure they meet performance and accuracy standards.
• Design and execute test cases to identify potential issues and biases in AI models.
• Collaborate with data scientists and engineers to refine models based on validation feedback.
• Develop automated testing frameworks for continuous validation of deployed models.
• Provide recommendations for improving model reliability, robustness, and fairness.

Requirements

• Strong experience in validating AI models and machine learning systems.
• Proficiency in programming languages such as Python, R, or SQL.
• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Knowledge of statistical techniques and performance metrics for model evaluation.
• Bachelor’s or Master’s in Computer Science, Data Science, or related field