Search for QA Engineer roles focusing on Generative AI in Austin, TX, requiring 3+ years of experience, familiarity with Python, and knowledge of testing frameworks like PyTest or Selenium.

Okay, I've searched for QA Engineer roles focusing on Generative AI in Austin, TX, requiring 3+ years of experience, proficiency in Python, and knowledge of testing frameworks like PyTest or Selenium. I found 45 positions for you to explore.

QA Engineer

Austin, TX

3 years + Experience

Python

PyTest

Selenium

Can you help me to analyze the job description and company culture?

Sure. Here's the analysis:

Job Analysis:

The QA Engineer - Generative AI role at Apple is fundamentally designed to enhance the performance and reliability of customer-facing support applications through rigorous testing and validation of generative AI technologies. The candidate is expected to implement comprehensive testing strategies that assure the functionality, accuracy, and ethical compliance of AI solutions. Key responsibilities involve collaborating with data scientists and ML engineers to define testing requirements, conducting performance and security evaluations, and ensuring the quality of AI training data. Given Apple's fast-paced innovation environment, this role requires not just technical proficiency but also a proactive mindset in identifying potential issues and advocating for an optimal customer experience. Success in this position will be characterized by the ability to build and maintain automated test suites, effectively communicate findings across teams, and contribute to reducing time-to-resolution for customer queries. The challenges may include navigating ambiguity in AI outcomes and ensuring stakeholder alignment on product quality standards.

Company Analysis:

Apple is a global leader in technology innovation, particularly known for pushing boundaries in consumer electronics, software, and services. This context shapes the QA Engineer role significantly; it isn't just about ensuring products work well but also about shaping experiences that align with Apple's brand ethos of excellence and seamless user service. The company culture appears to prioritize innovation, teamwork, and customer-centricity, which will require the candidate to be adaptable and visionary while maintaining strong collaborative ties with cross-functional teams. Within the organizational structure, this position is likely situated within a team focused on enhancing digital customer experiences, which may afford substantial visibility among leadership, providing opportunities for influence and contribution to high-stakes projects. The role aligns with Apple's strategy to remain at the forefront of utilizing AI to improve business outcomes and customer satisfaction, as highlighted by their commitment to generative AI initiatives.

Mock up some interview questions based on the job description.

Absolutely. Here are some mock interview questions that could come up:

Tell me about a time when you had to troubleshoot a significant quality issue in a project. How did you approach it?
Describe an experience where you collaborated across multiple teams. What challenges did you face, and how did you overcome them?
Can you provide an example of how you used data analysis to drive a decision in a previous role?
How do you ensure your testing strategies remain effective in a rapidly changing technological landscape?
How would you approach implementing a testing strategy for a new generative AI model that you're not familiar with?
What steps would you take to validate the fairness and ethical compliance of an AI-generated output?
Imagine you are testing a new AI feature that has returned inconsistent results across various user scenarios. What steps would you take to identify and rectify the issue?
Suppose you are asked to perform a load test for a new customer support app feature during high traffic hours. How would you structure your testing to ensure reliability?
Why are you interested in working at Apple, and what excites you about this role with generative AI?
Given the emphasis on customer experience at Apple, how do you prioritize user feedback in your testing processes?
What do you believe is the most critical aspect of managing quality in AI applications, and why?
Do you have any questions about how Apple approaches innovation and customer interaction in its products?
What aspects of our company's culture resonate most with your personal values?

Job Details

Overview Company

QA Engineer

Lensa

4 days ago

Highlight

OnsiteFull-time3+ yearsMid

Summary

Apple is seeking a QA Engineer - Generative AI, Support Apps to join their team in Austin, TX. The role involves driving platform and product testing for generative AI initiatives in customer-facing support apps.

About the Role

As a QA Engineer focused on Generative AI Product operations, you will design and implement robust testing strategies for Generative AI solutions, including functionality, performance, accuracy, and production sampling. You will collaborate with data scientists, ML engineers, and product teams to define testing requirements and identify potential risks. Responsibilities include developing and maintaining automated test suites for AI/ML pipelines and APIs, validating AI generative solutions for bias, fairness, and ethical compliance, and performing load, stress, and security testing.

About You

Required:

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.
Experience leading projects and coordinating quality strategies across teams or functions.

Preferred:

Master's or equivalent experience in Computer Science, Software Engineering, or an MBA.
Project management certification.
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.

Lensa

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Austin, TX