Key Responsibilities:

• Lead AI/ML Initiatives: Develop, evaluate, and validate AI/ML models that support and enhance clinical, operational, and financial processes across the UCLA Health system. Lead projects end to end, from framing the problem to delivering high-quality outputs on schedule.
• Enhance MLOps, LLMOps & Responsible AI Governance: Apply and advance our ML and LLM operations paradigms and uphold our AI governance framework, ensuring ethical and scalable AI practices are integrated into every model developed and deployed.
• Bias & Fairness Testing: Conduct rigorous statistical bias and fairness evaluation strategies for models developed by UCLA Health teams and external vendors, ensuring equitable AI solutions that reflect the diversity of our patient population.
• Deliver Actionable Insights: Interpret model outputs and effectively communicate insights to stakeholders at various technical levels. Use strong storytelling, visualization, and communication skills to drive alignment and impact across clinical, operational, and executive audiences.
• Drive Collaboration & Innovation: Foster a culture of collaboration across departments by sharing knowledge, best practices, and new developments in AI/ML. Operate effectively in agile, cross-functional teams and help structure clear, actionable work plans to guide team execution.
• Leverage Advanced AI/ML Techniques: Utilize large language models (LLMs), generative AI, and agentic AI frameworks to solve complex healthcare challenges in an ever-evolving technological landscape.
• Identify AI/ML Solutions for Stakeholder Needs: Collaborate with clinical, financial, and operational teams to identify AI/ML opportunities that address key business challenges and improve outcomes. Guide project scoping and execution to ensure relevance, feasibility, and impact.

Seeking a candidate with:

• Extensive hands-on experience with large language models (LLMs) and generative AI techniques
• Strong understanding of MLOps, LLMOps, responsible AI governance, and bias/fairness testing methodologies
• Excellent communication and stakeholder engagement skills, with the ability to explain complex technical concepts and influence decision-making
• Demonstrated experience leading data science projects with structured work plans, clear milestones, and timely, high-quality deliverables
• Deep knowledge of healthcare systems and an understanding of clinical, financial, and operational challenges in the healthcare industry
• Ability to work in an innovation-driven, agile environment, continuously learning and applying the latest AI/ML technologies with strong statistical and experimental foundations

Additional Information:

• Epic Certification: Selected candidates will be required to complete Epic certifications within 6 months of hire if not currently certified.
• Application Instructions: Please upload your cover letter along with your resume into a single PDF file.
• Selection Timeline: We will be reviewing applications throughout May 2026.