Senior QA Engineer - AI/ML

Job Requirements

At Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster.

Looking for an AI Quality Engineer who will be responsible for validating cutting-edge artificial intelligence solutions across various domains, including generative AI, conversational AI, and predictive AI.

Key Responsibilities

• 5 to 8 years of experience in Manual and Automation testing
• Experience in data quality analysis, profiling, and feature validation
• Understanding of model evaluation metrics and validation of performance results
• Ability to interpret model behavior and explainability outputs
• Experience testing AI APIs and services built using FastAPI or Flask
• Familiarity with cloud-based AI deployments, preferably AWS SageMaker
• Understanding of production ML lifecycle, including deployment validation and monitoring
• Strong analytical, problem-solving, and communication skills for cross-functional collaboration
  
  

We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.

We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.

Work Experience

• Experience in testing and validating AI/ML solutions including Generative AI, Conversational AI, and Predictive models
• Strong understanding of how ML models are built end-to-end (data preparation, feature engineering, training, validation, tuning)
• Knowledge of core ML algorithms and model types (regression, classification, clustering, tree-based models, neural networks, transformers)
• Proficiency in Python for AI test automation, data analysis, and model output validation
• Hands-on experience with pandas, NumPy, and scikit-learn for data and model validation
• Experience in data quality analysis, profiling, and feature validation
• Understanding of model evaluation metrics and validation of performance results
• Ability to interpret model behavior and explainability outputs
• Experience testing AI APIs and services built using FastAPI or Flask
• Familiarity with cloud-based AI deployments, preferably AWS SageMaker
• Understanding of production ML lifecycle, including deployment validation and monitoring
• Strong analytical, problem-solving, and communication skills for cross-functional collaboration