Pay
$70-$75(the pay rate may differ depending on your skills, education, experience, and other qualifications)
Featured Benefits
• Medical Insurance in compliance with the ACA
• 401(k)
• Sick leave in compliance with applicable state, federal, and local laws
Job Description:
We are seeking a highly skilled and experienced Senior QA Engineer with a specialized focus on testing machine learning (ML) models. The ideal candidate will play a critical role in ensuring the quality, reliability, and performance of our ML-driven applications. You will collaborate with data scientists, developers, and product managers to design and implement test strategies for ML models, ensuring they meet functional and performance requirements.
Key Responsibilities:
• Proven ability to collaborate effectively with multi-disciplinary teams in a fast-paced, dynamic environment.
• Identify, document, and track defects and inconsistencies in ML models and provide detailed, actionable feedback to data science and engineering teams for resolution.
• Design and implement comprehensive testing strategies for ML models, ensuring reproducibility and accuracy.
• Develop automated testing frameworks to validate ML pipelines, including data preprocessing, model training, inference, and deployment.
• Conduct functional, stress, adversarial, and robustness testing of computer vision models.
• Evaluate model fairness, bias, and explainability, ensuring compliance with ethical AI guidelines.
• Develop benchmark datasets and synthetic test cases for edge cases, adversarial examples, and domain shifts.
• Monitor and validate model performance across different environments, hardware accelerators (GPU, TPU), and cloud platforms.
• Work with data engineers to ensure the integrity and quality of training data.
• Implement CI/CD testing pipelines for machine learning models to enable continuous integration and monitoring.
• Investigate and troubleshoot performance issues related to inference speed, memory consumption, and accuracy degradation.
• Document test methodologies, findings, and improvement recommendations for ML workflows.
Qualifications & Skills:
• 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 in ML/AI model testing.
• Strong understanding of computer vision models (CNNs, transformers, object detection, segmentation).
• Proficiency in Python and experience with ML frameworks like TensorFlow, PyTorch, OpenCV.
• Experience with ML model evaluation metrics, AUC, F1-score, precision-recall, confusion matrices.
• Familiarity with adversarial testing, explainable AI (XAI), and bias detection in models.
• Hands-on experience with model deployment testing in cloud and edge computing environments.
• Experience with Docker, Kubernetes, and ML model versioning tools (MLflow, DVC, or similar).
• Knowledge of MLOps best practices and CI/CD for machine learning.
• Experience in automating model performance monitoring in production is a plus.
• Strong analytical and debugging skills with a research-oriented mindset.
