QA Engineer - Generative AI, Support Apps

Key Skills

Java Programming, Python Programming, Azure, AWS, Aartificial intelligence, Machine learning techniques, Google Cloud Platform (GCP), MLflow, Github, MLOps tools, Large Language Models - LLMs

Job Description

As 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 Qualifications

• Bachelor's in Computer Science, Software Engineering or similar field of study
• 3+ 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 capacity

Preferred Qualifications

• Master's or equivalent experience in Computer Science, Software Engineering, or an MBA is a plus
• Understanding 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 systems
• Expert in the use of industry-standard data analysis and reporting tools including Tableau

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $112,900 and $234,700, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.