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Clinical Ai Informatics Jobs in California (NOW HIRING)

Clinical Consultant

San Francisco, CA · On-site

$150 - $200/hr

We combine expertise in AI with deep clinical knowledge to develop safe, trustworthy systems that ... Salary Range The range for the Clinical Informatics Consultant is approximately $150-200/hr.

Clinical Product Manager

San Francisco, CA · On-site +1

$200K - $300K/yr

... informatics or health IT implementation * Understanding of HIPAA compliance, healthcare data privacy, and FDA regulations for clinical software * Experience with prompt engineering, LLMs, or AI ...

We are on a mission to revolutionize healthcare with cutting-edge, AI-powered software designed to ... Our platform is already the core backbone of health systems today, transforming clinical and ...

Showing results 21-40

Clinical Ai Informatics information

See California salary details

$51.3K

$102.2K

$161.9K

How much do clinical ai informatics jobs pay per year?

As of Aug 7, 2026, the average yearly pay for clinical ai informatics in California is $102,240.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,000.00 and $114,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a clinical AI informatics specialist?

To thrive as a Clinical AI Informatics Specialist, you need a strong background in healthcare, data analysis, and artificial intelligence, typically supported by degrees in health informatics, computer science, or related fields. Familiarity with clinical information systems, machine learning tools, programming languages like Python or R, and relevant certifications (e.g., Certified Professional in Healthcare Information and Management Systems) is highly valuable. Strong problem-solving abilities, communication skills, and a collaborative mindset help bridge the gap between technical teams and clinical stakeholders. These competencies ensure effective implementation of AI solutions that improve patient outcomes and streamline healthcare operations.

What is the difference between Clinical Ai Informatics vs Clinical Data Analyst?

AspectClinical Ai InformaticsClinical Data Analyst
Required CredentialsHealthcare background, data science or informatics certifications, programming skillsHealthcare or data analysis degrees, statistical knowledge, data management skills
Work EnvironmentHospitals, healthcare tech companies, research institutionsHospitals, clinics, healthcare organizations, research settings
Employer & Industry UsageHealthcare technology firms, hospitals, research institutionsHealthcare providers, clinics, health insurance companies
Common Search & Comparison IntentUnderstanding roles involving AI in clinical settingsAnalyzing clinical data for insights and reporting

Clinical Ai Informatics focuses on integrating artificial intelligence into healthcare workflows, requiring expertise in AI, programming, and healthcare systems. In contrast, Clinical Data Analysts primarily analyze clinical data to generate reports and insights, often with a focus on statistical analysis and data management. Both roles are vital in healthcare but differ in technical focus and responsibilities.

How does a clinical AI informatics professional typically collaborate with clinicians and IT teams to implement AI-driven solutions in healthcare settings?

Clinical AI Informatics professionals serve as a bridge between clinical staff and IT departments, facilitating the integration of AI tools into healthcare workflows. They work closely with clinicians to understand patient care needs and ensure that AI solutions align with clinical protocols. Simultaneously, they collaborate with IT teams to address data integration, system interoperability, and regulatory compliance. Effective communication and stakeholder management are critical, as these professionals must translate technical requirements into practical, patient-centered applications.

What is clinical AI informatics?

Clinical AI Informatics is a specialized field that combines artificial intelligence (AI) and informatics to improve healthcare delivery, diagnostics, and patient outcomes. Professionals in this area develop, implement, and manage AI tools and data systems that help clinicians analyze complex medical data and make evidence-based decisions. Their work includes integrating AI algorithms into electronic health records, supporting predictive analytics, and ensuring data privacy and regulatory compliance. By leveraging advanced technologies, Clinical AI Informatics aims to make healthcare more efficient, accurate, and personalized.
What job categories do people searching Clinical Ai Informatics jobs in California look for? The top searched job categories for Clinical Ai Informatics jobs in California are:
What cities in California are hiring for Clinical Ai Informatics jobs? Cities in California with the most Clinical Ai Informatics job openings:
Infographic showing various Clinical Ai Informatics job openings in California as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $102,240 per year, or $49.2 per hour.

AI Engineer (AI Accelerator Program)

University of California San Francisco

San Francisco, CA

$62.25 - $85/hr

Full-time

Re-posted 24 days ago


University Of California San Francisco rating

7.8

Company rating: 7.8 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

228th of 616 rated colleges and universities


Job description

Job Summary:

This position requires 1 day onsite per week, based on business needs, this may increase. 

UCSF Health is seeking a highly skilled AI Engineer to design, build, and deploy scalable AI-driven applications that improve clinical operations, patient care, and health system efficiency. This role spans the full AI lifecycle, including data pipeline development, model training and evaluation, and deployment of machine learning and generative AI solutions on modern cloud platforms. 

The AI Engineer will translate emerging technologies, including large language models (LLMs), into production-ready tools that integrate with healthcare systems. Responsibilities include building robust data pipelines, deploying machine learning and generative AI models, and developing APIs or web-based applications that enable seamless use in clinical and operational workflows. This role works closely with clinicians, data scientists, and IT teams to deliver solutions that are reliable, secure, and scalable. 

 Competitive applicants for this position are software, data, or machine learning engineers with 5+ years of experience building AI systems in production. They have strong skills in Python and SQL, and hands-on experience with MLOps, CI/CD, and cloud platforms (e.g., GCP, AWS, or Azure). Candidates should be comfortable developing and maintaining data pipelines, deploying machine learning or generative AI models, and building APIs or lightweight web applications, with the ability to work across the stack and deliver practical, user-facing solutions in a healthcare environment. 

Department Overview:

The Health AI team is part of the larger UCSF Health IT team and supports the development, implementation, and monitoring of artificial intelligence, machine learning, and other analytical tools, improving patient care, clinician experience, and health system operations. The team's expertise spans data science, machine learning, software/data engineering, business, nursing informatics, and medical informatics.   

UCSF Health IT provides clinical and informatics leadership to achieve the strategic priorities of UCSF Health, as enabled by technology. Health IT is a multidisciplinary team of clinicians and technology professionals that partners with clinical, business, and technology leaders throughout the organization, using information technology to improve the quality, safety, and value of care, and the patient and provider experience, for UCSF and its partner organizations. 

About UCSF

The University of California, San Francisco (UCSF) is a leading university dedicated to promoting health worldwide through advanced biomedical research, graduate-level education in the life sciences and health professions, and excellence in patient care. It is the only campus in the 10-campus UC system dedicated exclusively to the health sciences. We bring together the world's leading experts in nearly every area of health. We are home to five Nobel laureates who have advanced the understanding of cancer, neurodegenerative diseases, aging and stem cells.

Pride Values

UCSF is a diverse community made of people with many skills and talents. We seek candidates whose work experience or community service has prepared them to contribute to our commitment to professionalism, respect, integrity, diversity and excellence - also known as our PRIDE values.

In addition to our PRIDE values, UCSF is committed to equity - both in how we deliver care as well as our workforce. We are committed to building a broadly diverse community, nurturing a culture that is welcoming and supportive, and engaging diverse ideas for the provision of culturally competent education, discovery, and patient care. Additional information about UCSF is available here.

Join us to find a rewarding career contributing to improving healthcare worldwide.

Equal Employment Opportunity

The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.

Salary Information

The final salary and offer components are subject to additional approvals based on UC policy.

Your placement within the salary range is dependent on a number of factors including your work experience and internal equity within this position classification at UCSF. For positions that are represented by a labor union, placement within the salary range will be guided by the rules in the collective bargaining agreement.

To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html

Required Qualifications:

  • Bachelor's degree in related area and / or equivalent experience / training. 
  • 5 years of experience in positions of increasing responsibility designing, implementing, and maintaining complex AI/ML applications. 
  • Experience with data analysis and machine learning tools such as Jupyter, Pandas, scikit-learn, Numpy/Scipy, PyTorch, etc. 
  • Demonstrated advanced knowledge of full software development lifecycle 
  • Advanced experience with Python; ability to write clean, efficient, and production-level Python code 
  • Advanced experience with SQL (e.g., SQLServer, PostgreSQL)   
  • Demonstrated experience deploying, monitoring, and maintaining AI/ML models and pipelines 
  • Experience designing and developing APIs or microservices to support AI/ML applications 
  • Familiarity with web application development frameworks (e.g., React, JavaScript/TypeScript) or integrating backend systems with user-facing applications 
  • Experience with large language models (LLMs), including prompt engineering, evaluation, and production deployment 
  • Experience with real-time or streaming data processing systems and low-latency inference architectures 
  • Demonstrated effective communication and interpersonal skills 
  • Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization 
  • Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines 
  • Demonstrated broad problem-solving skills 
  • Demonstrated ability to interface with management on a regular basis 
  • Excellent project leadership and management skills. 

Preferred Qualifications:

  • Master's degree or PhD in Computer Science, Computer Engineering, or related area and/or equivalent experience/training. 
  • Epic Clarity or Clinical Data Model 
  • Familiar with data visualization tools (e.g., Tableau) 
  • Experience with Epic data structures 

%  

of time 

Essential Function (Yes/No

 

Key Responsibilities 

(To be completed by Supervisor) 

10 

Applies advanced software concepts to plan, design, develop, modify, debug, deploy and evaluate highly complex software for functional areas. Analyzes existing highly complex software or works to formulate logic and devises algorithms for new highly complex software systems. Performs highly complex data analysis and tests / debugs highly complex software, working directly with management. Initiates, analyzes, designs and applies highly complex data sources. Applies and enforces complex programming security practices. 

10 

Specifies, develops and executes complex test plans. Develops conversion and system implementation plans. Performs or directs highly complex data modeling, performance and integration testing and builds interfaces. Determines source code control techniques and configuration management design and changes. 

Prepares and approves or obtains approval for system and programming documentation. Initiates and oversees changes in development, maintenance and system standards. Sets the technical requirements for complex software specifications. 

Understands and applies industry practices, community standards and department policies and procedures in depth. May serve as technical lead for multiple software development projects of moderate to broad scope. May lead a team of software development professionals. Enforces project plans. 

15 

Build and maintain data integration (with SQL databases or APIs) and data processing and transformation pipelines to support the development and implementation of AI/ML tools 

15 

Identify and build systems for implementation, monitoring, and maintenance of AI/ML tools using modern MLOps practices including CI/CD, model versioning, and cloud-native deployment.  

Collaborate with data scientists and researchers to design and implement highly complex metrics and processes to automatically monitor AI/ML tools for safety, potential bias or drift, performance, and validity. 

10 

Design and develop APIs, services, or lightweight web applications to enable integration of AI/ML and generative AI capabilities into clinical and operational workflows. 

15 

Develop and deploy generative AI solutions (e.g., LLM-based systems), including prompt engineering, retrieval-augmented generation (RAG), and evaluation frameworks for unstructured data. 

10 

Design and implement highly complex real-time or near real-time data processing and inference systems to support AI/ML and generative AI applications. Develop scalable, event-driven architectures and ensure reliable, low-latency integration of AI capabilities into production clinical and operational workflows 

100% 

(To update total %, enter the amount of time in whole numbers (without the % symbol - e.g., 15, 20) then highlight the total sum (e.g., 1%) at the bottom of the column and press F9. The total sum should add up to 100%.) 


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