Developing and implementing quality assurance strategies for AI/ML initiatives in a Good Manufacturing Practice (GMP) environment to ensure the reliability, accuracy, and overall quality of AI/ML solutions.
Requirements
- PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field with 8+ years of progressive experience in developing and deploying machine learning models and AI solutions
- Hands-on experience with NLP, deep learning frameworks (e.g., TensorFlow, PyTorch), and deploying models in production environments
- Deep understanding of machine learning algorithms, statistical modeling, and data mining techniques, with a focus on quality validation
- Experience with quality assurance methodologies applied to Large Language Models (LLMs) and their integration
- Experience with quality assessment and validation of reinforcement learning applications for autonomous systems
- Familiarity with quality assurance tools and best practices for cloud-based AI/ML platforms
- Publications or presentations related to AI/ML quality or testing
Responsibilities
- Establish and lead the overall quality strategy and framework for all AI/ML initiatives across the organization
- Define and implement comprehensive quality assurance processes and methodologies throughout the AI/ML lifecycle
- Develop and enforce quality standards for robust systems and processes across the entire AI model lifecycle
- Define quality metrics and oversee the crafting and optimization of algorithms for various applications
- Establish quality assurance processes for leveraging machine learning methodologies to analyze historical data and predict future trends
- Define quality standards and oversee the development and implementation of deep learning models for complex applications
- Establish quality assurance measures for the deployment of reinforcement learning algorithms used to train autonomous systems
Other
- Excellent communication, presentation, and interpersonal skills, with the ability to explain complex technical concepts related to AI quality to both technical and non-technical audiences
- Willingness to travel to domestic and international sites as required
- Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field with 12+ years of progressive experience in developing and deploying machine learning models and AI solutions
- Associate's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field with 14+ years of progressive experience in developing and deploying machine learning models and AI solutions
- High School Degree with 16+ years of progressive experience in developing and deploying machine learning models and AI solutions
