AI back

Key Responsibilities

• Conduct comprehensive testing of AI solutions, including the identification and analysis of failure scenarios, and implement refactoring strategies to prevent future issues.
• Collaborate effectively with development teams and Product Owners to pinpoint the root causes of defects and implement preventative measures.
• Drive the adoption and implementation of test automation, including unit tests, integration tests, and functional tests, to guarantee the efficiency and reliability of AI products.
• Proactively identify and report bugs and defects within AI solutions, managing their lifecycle through to resolution.
• Validate that AI products meet stringent quality standards, ensuring robustness and identifying opportunities for continuous improvement.

Required Qualifications

Candidates should possess a Bachelor's Degree and 2-6 years of relevant experience, including:

• Day-to-day test execution and failure analysis, with experience in opening and closing defects.
• Proficiency in Linux system administration.
• Hands-on experience testing AI frameworks such as PyTorch, TensorFlow, or similar.
• Experience testing GPU/CUDA based projects and AI accelerators with their associated ecosystems.
• A solid understanding of Machine Learning and Deep Learning technologies.
• Expertise in automating REST APIs using Python's `requests` library.
• Demonstrated experience with test automation tools and methodologies, covering unit, integration, and functional testing.
• Proven experience working with cross-functional teams to identify and resolve defects in AI solutions.

Preferred Qualifications

• In-depth knowledge of Deep Learning and AI frameworks.
• Strong Linux system programming skills.
• Experience creating CI/CD pipelines and jobs in Jenkins.
• Familiarity with Python scripts, Bash, and Groovy scripts within Jenkins pipelines.
• Experience with IBM Z systems is considered an advantage.