Associate SDET Specialist

Design, develop, implement, test, and maintain automated test suites and frameworks for AI/ML pipelines. Collaborate closely with ML engineers and data scientists to understand model architectures and data workflows. Develop and execute test plans, test cases, and test scripts to identify software defects in AI/ML applications. Ensure end-to-end quality of AI/ML solutions, including data integrity, model performance, and system integration. Implement continuous integration and continuous deployment (CI/CD) processes for ML pipelines. Conduct performance and scalability testing for AI/ML systems. Document and track software defects using bug-tracking systems, and report issues to development teams. Participate in code reviews and provide feedback on testability and quality. Help foster a culture of quality and continuous improvement within the ML engineering group. Stay updated with the latest trends and best practices in AI/ML testing and quality assurance. Must Haves: Bachelor s degree in Computer Science, Engineering, or a related field. 2+ years of experience in quality assurance, specifically testing AI/ML applications. Experience with the following: Strong programming skills in Python (experience with libraries like PyTest or unittest). Familiarity with machine learning frameworks (TensorFlow, PyTorch, or scikit-learn). Experience with test automation tools and frameworks. Knowledge of CI/CD tools (Jenkins, GitLab CI, or similar). Experience with containerization technologies like Docker and orchestration systems like Kubernetes. Proficient in Linux operating systems. Familiarity with version control systems like Git. Strong understanding of software testing methodologies and best practices. Excellent analytical and problem-solving skills. Excellent communication and collaboration skills. Bonus Attributes: Experience with testing data pipelines and ETL processes. Cloud platform experience; GCP, AWS or Azure are acceptable. Knowledge of big data technologies like Apache Spark, Kafka, or Airflow. Experience with performance testing tools. Understanding of data science concepts and statistical analysis. Certifications in software testing or cloud technologies. Abilities: Ability to work with a high level of initiative, accuracy, and attention to detail. Ability to prioritize multiple assignments effectively. Ability to meet established deadlines. Ability to successfully, efficiently, and professionally interact with staff and customers. Excellent organization skills. Critical thinking ability ranging from moderately to highly complex. Flexibility in meeting the business needs of the customer and the company. Ability to work creatively and independently with latitude and minimal supervision. Ability to utilize experience and judgment in accomplishing assigned goals. Experience in navigating organizational structure.