Director, Artificial Intelligence and Machine Learning (AI/ML) Quality Oversight

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Job Description

We are seeking a highly experienced Director of Artificial Intelligence and Machine Learning (AI/ML) Quality Oversight to establish and lead the quality assurance strategy for our AI/ML initiatives specifically within a Good Manufacturing Practice (GMP) environment. This pivotal role will be responsible for defining implementing and maintaining rigorous quality standards and processes across the entire AI/ML lifecycle from model development and deployment to ongoing monitoring and governance ensuring the reliability accuracy ethical compliance and overall quality of our AI/ML solutions in this regulated context. The Director will foster trust and drive responsible innovation while adhering to the stringent requirements of GMP.

Job Responsibilities

AI/ML Quality Strategy and Oversight:

• Establish and lead the overall quality strategy and framework for all AI/ML initiatives across the organization ensuring adherence to quality principles and standards.

• Define and implement comprehensive quality assurance processes and methodologies throughout the AI/ML lifecycle from data acquisition and model development to deployment and monitoring.

• Serve as the primary point of contact and subject matter expert for AI/ML qualityrelated policies procedures and guidelines.

• Develop and implement training curricula and materials to support the effective rollout and adoption of AI/ML quality standards policies and procedures across relevant teams.

Quality Assurance in Model Development & Deployment:

• Define and oversee quality gates and validation processes for the creation and implementation of machine learning models addressing diverse business needs.

• Ensure the quality and reliability of Natural Language Processing (NLP) solutions developed for tasks including sentiment analysis and automation.

• Establish quality assurance measures for the integration of Large Language Models (LLMs) in advanced AI applications such as chatbots language generation and custom AI solutions.

Quality in AI Model Lifecycle Management:

• Develop and enforce quality standards for robust systems and processes across the entire AI model lifecycle including continuous model monitoring retraining strategies and performance optimization.

AI Governance Ethics and Quality Compliance:

• Develop and implement quality checks within comprehensive frameworks for responsible and compliant AI utilization ensuring adherence to ethical standards and regulatory requirements.

Algorithm Quality and Performance:

• Define quality metrics and oversee the crafting and optimization of algorithms for various applications ensuring accuracy speed and scalability.

Quality in Predictive Analytics & Forecasting:

• Establish quality assurance processes for leveraging machine learning methodologies to analyze historical data and predict future trends ensuring the reliability of insights for strategic decisionmaking.

Quality in Deep Learning Applications:

• Define quality standards and oversee the development and implementation of deep learning models for complex applications such as image and speech recognition and autonomous systems.

Quality in Reinforcement Learning for Autonomous Systems:

• Establish quality assurance measures for the deployment of reinforcement learning algorithms used to train autonomous systems for realtime decisionmaking.

AI Model Explainability Interpretability and Trust:

• Champion the implementation of quality checks for techniques ensuring the explainability and interpretability of AI models fostering trust and understanding among both technical and nontechnical stakeholders.

Basic Qualifications:

• PhD in degree in Computer Science Artificial Intelligence Machine Learning or a related quantitative field with 8years of progressive experience in developing and deploying machine learning models and AI solutions with a strong emphasis on quality assurance and oversight OR

• Masters degree in Computer Science Artificial Intelligence Machine Learning or a related quantitative field with 10years of progressive experience in developing and deploying machine learning models and AI solutions with a strong emphasis on quality assurance and oversight OR

• Bachelors degree in Computer Science Artificial Intelligence Machine Learning or a related quantitative field with 12years of progressive experience in developing and deploying machine learning models and AI solutions with a strong emphasis on quality assurance and oversight OR

• Associates degree in Computer Science Artificial Intelligence Machine Learning or a related quantitative field with 14years of progressive experience in developing and deploying machine learning models and AI solutions with a strong emphasis on quality assurance and oversight OR

• High School Degree with 16 yearsof progressive experience in developing and deploying machine learning models and AI solutions with a strong emphasis on quality assurance and oversight.

Preferred Qualifications:

• Advanced degree in Computer Science Artificial Intelligence Machine Learning or a related quantitative field.

• 10 years of progressive experience in developing and deploying machine learning models and AI solutions with a strong emphasis on quality assurance and oversight.

• Deep understanding of machine learning algorithms statistical modeling and data mining techniques with a focus on quality validation.

• Handson experience with NLP deep learning frameworks (e.g. TensorFlow PyTorch) and deploying models in production environments with a qualitycentric approach.

• Strong understanding of AI ethics governance responsible AI practices and their implications for quality assurance.

• Excellent communication presentation and interpersonal skills with the ability to explain complex technical concepts related to AI quality to both technical and nontechnical audiences.

• 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.

• Experience in developing and implementing quality management systems for the AI model lifecycle.

• Familiarity with quality assurance tools and best practices for cloudbased AI/ML platforms.

• Publications or presentations related to AI/ML quality or testing.

• Relevant certifications in quality assurance or AI/ML.

• Willingness to travel to domestic and international sites as required.

For additional benefits information visit:

Eligible employees may participate in benefit plans subject to the terms and conditions of the applicable plans.

Kite is a biopharmaceutical company engaged in the development of innovative cancer immunotherapies with a goal of providing rapid longterm durable response and eliminating the burden of chronic care. The company is focused on chimeric antigen receptor (CAR) and T cell receptor (TCR) engineered cell therapies designed to empower the immune systems ability to recognize and kill tumors. Kite is based in Santa Monica CA. For more information on Kite please visit . Sign up to follow @KitePharma on Twitter at jobs in the United States:

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