What are the responsibilities and job description for the Sr Quality Engineer AI Machine Learning Models position at ClinDCast LLC?
Job Description :
We are seeking a Machine Learning QA Engineer with a strong background in testing ML / AI models to ensure robustness, reliability, and fairness. The ideal candidate will have expertise in computer vision models, ML frameworks, and MLOps best practices.
Responsibilities :
Design and execute comprehensive test strategies for ML models, focusing on performance, accuracy, bias detection, and adversarial testing.
Validate computer vision models (CNNs, transformers, object detection, segmentation) to ensure they meet quality standards.
Develop and automate test cases for ML pipelines using frameworks such as TensorFlow, PyTorch, and OpenCV.
Evaluate model performance using AUC, F1-score, precision-recall, confusion matrices, and other metrics.
Conduct explainability analysis (XAI) to assess and interpret model decisions.
Test model deployment in cloud and edge computing environments, ensuring smooth integration and performance.
Implement ML model versioning using tools like MLflow, DVC, or similar.
Work with Docker, Kubernetes, and CI / CD pipelines to optimize ML testing processes.
Collaborate with data scientists, engineers, and DevOps teams to enhance ML testing strategies.
Monitor model performance in production and contribute to automation for continuous evaluation.
Requirements :
Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field.
5 years of experience in QA, with at least 3 years focused on ML / AI model testing.
Strong proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, and OpenCV.
Expertise in ML evaluation metrics and model validation techniques.
Hands-on experience in adversarial testing, explainable AI (XAI), and bias detection.
Familiarity with MLOps best practices and CI / CD workflows for ML.
Experience with Docker, Kubernetes, and ML model deployment testing.
Strong analytical, debugging, and research-oriented mindset.
Preferred Qualifications :
Experience in automating model performance monitoring in production.
Knowledge of edge AI and real-time model testing.
Flexible work from home options available.
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