Holistic Machine Learning Quality Assurance and Data Validation Specialist
3 days ago
About the Role
We're seeking a highly skilled Machine Learning QA Engineer to join our Machine Learning & Data organization. As a member of our team, you'll play a crucial role in bringing 'AI first' products to life across various product offerings. Your responsibilities will include implementing a holistic test strategy for data and model evaluation, applying best practices into the AI/ML development cycle, and supporting ML Engineers in Model Evaluation, Data Quality Validation, and Model Monitoring.
Your Key Responsibilities
- Develop and implement a comprehensive test strategy for data and model evaluation, as well as the fundamental ML pipeline testing and monitoring.
- Apply best practices into the AI/ML development cycle to ensure high stability, issue discovery, and low maintenance.
- Support ML Engineers in Model Evaluation (e.g., Error Analysis), Data Quality Validation, Data Annotation, and Model Monitoring to guarantee high-quality AI-driven products.
- Collaborate closely with ML Engineers, MLOps Engineers, and other QA engineers to ensure a common understanding and implementation of best practices.
- Contribute to the growth and continuous improvement of quality and testing processes within the organization.
About You
What We're Looking For
- Strong experience in Quality Assurance and Test Automation with a focus on AI/ML.
- Understanding of QA methodologies, tools, and processes.
- Strong experience in statistical analysis or machine learning algorithms, natural language processing, and LLMs.
- Experience in AI/ML System Design and the lifecycle of ML Models.
Working at Workday Peakon
We're committed to creating an inclusive work environment that values diversity, equity, and inclusion. Our flexible work arrangements enable our teams to deepen connections, maintain a strong community, and do their best work. Join us and be part of a collaborative work environment that's dedicated to helping you grow professionally and personally.
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