SummaryPosted: Jan 22, 2025Role Number:200587866Imagine what you could do here. At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish. From day one, you’ll have the opportunity to make meaningful contributions to the big picture inside our AppleCare Digital team. AppleCare Digital seeks a QA Engineer to help drive platform and product testing for generative AI initiatives in our customer-facing support apps. The role will focus on implementing and analyzing the performance of generative AI solutions to improve customer experience, increase issue resolution, and achieve business goals. It requires process-oriented creative thinking and the ability to cut through ambiguity. The ideal candidate will have a proactive approach to identifying issues, strong analytical and problem-solving skills, an obsession with customer experience, and hands-on experience applying generative AI technology to end-customer interactions with proven, high-quality results.DescriptionDescriptionAs a QA Engineer focused on Generative AI Product operations, we design and implement robust testing strategies for Generative AI solutions. Testing will include functionality, performance, accuracy and production sampling. Using the latest emerging AI technology, we test feature quality and assess customer experience. We will also collaborate with data scientists, ML engineers, and product teams to define testing requirements and identify potential risks. We develop and maintain automated test suites for AI/ML pipelines and APIs. Test data preprocessing pipelines and ensure data quality for AI model training. We validate AI generative solutions for bias, fairness, and ethical compliance. Perform load, stress, and security testing on solutions to ensure reliability. In this role, you will be the SME for auditing Generative AI quality across the AppleCare Digital platform. Collaboration, detailed troubleshooting, effective communication of issues, and timely resolution are critical skills required to succeed.Minimum QualificationsMinimum QualificationsBachelor's in Computer Science, Software Engineering or similar field of study3+ years of experience in QA engineering, with a focus on AI/ML systems.Strong programming skills in Python, Java, or another relevant language.Hands-on experience with testing frameworks like PyTest, Selenium, or JUnit.Familiarity with ML frameworks such as TensorFlow, PyTorch, or Hugging Face.Understanding of RESTful APIs and tools like Postman for API testing.Knowledge of CI/CD tools like Jenkins, GitHub Actions, or GitLab.Experience in validating Generative AI models (e.g., GPT, DALL-E)Knowledge of NLP, computer vision, or multimodal models.Familiarity with synthetic data testing techniques.Experience in verifying training data integrity and bias detection.Familiarity with data annotation tools and quality control processes.Experience with prompt engineering and LLMs in a hands-on capacityKey QualificationsKey QualificationsPreferred QualificationsPreferred QualificationsMaster's or equivalent experience in Computer Science, Software Engineering, or an MBA is a plusUnderstanding of LLM fine-tuning and evaluation metrics (e.g., BLEU, ROUGE, F1-score).Knowledge of XAI (explainable AI) tools (e.g., SHAP, LIME).Familiarity with regulations like GDPR and AI ethics frameworks.Experience with cloud platforms (AWS, Azure, Google Cloud) and MLOps tools (e.g., Kubeflow, MLflow).Proficiency in load testing tools like JMeter or Locust.Experience with security best practices in AI systemsExpert in the use of industry-standard data analysis and reporting tools including TableauEducation & ExperienceEducation & ExperienceAdditional RequirementsAdditional RequirementsMore

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