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Medical Coding Artificial Intelligence Jobs in California

KLA

Artificial Intelligence Engineer

Milpitas, CA · On-site

$140K - $238K/yr

... medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program ...

Orbotech

Artificial Intelligence Engineer

Milpitas, CA · On-site

$140K - $238K/yr

... medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program ...

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All JobsMedical Coding Artificial Intelligence JobsMedical Coding Artificial Intelligence Jobs in California

Medical Coding Artificial Intelligence information

What is Medical Coding Artificial Intelligence?

Medical Coding Artificial Intelligence refers to the use of AI technologies to automate and improve the medical coding process in healthcare. AI systems can analyze clinical documentation, extract relevant information, and assign appropriate codes for diagnoses and procedures. This technology helps healthcare providers increase accuracy, reduce manual errors, streamline billing, and ensure compliance with regulations. By leveraging AI, organizations can save time and resources while enhancing the quality of patient data management.

How do professionals in Medical Coding Artificial Intelligence typically collaborate with healthcare providers and IT teams?

Professionals working in Medical Coding Artificial Intelligence frequently interact with both healthcare providers and IT teams to develop and refine AI models that accurately interpret medical documentation. This collaboration involves understanding clinical workflows, ensuring data privacy compliance, and translating medical terminology into machine-readable formats. Regular meetings and cross-functional teamwork help align the AI solutions with real-world clinical needs and regulatory standards, making strong communication skills essential for success in this role.

What are the key skills and qualifications needed to thrive in Medical Coding Artificial Intelligence, and why are they important?

To excel in Medical Coding Artificial Intelligence, you need a strong background in medical coding, familiarity with healthcare terminology, and expertise in AI or machine learning, often supported by degrees in health informatics, computer science, or related certifications. Experience with coding systems like ICD-10, CPT, and proficiency in AI tools, programming languages (such as Python), and natural language processing platforms are typically required. Strong analytical thinking, attention to detail, and effective collaboration skills help professionals bridge the gap between clinical data and technical solutions. These competencies are crucial for developing, optimizing, and deploying AI systems that improve the accuracy and efficiency of medical coding in healthcare organizations.

What is the difference between Medical Coding Artificial Intelligence vs Medical Coding Specialist?

AspectMedical Coding Artificial IntelligenceMedical Coding Specialist
CredentialsNone required, relies on algorithmsCertification (e.g., CPC, CCS)
Work EnvironmentAutomated systems, software platformsHospitals, clinics, healthcare offices
Industry UsageAssists or automates coding tasksPerforms manual coding and audits
Search/Comparison IntentUnderstanding AI role in codingManual coding skills and certification

Medical Coding Artificial Intelligence primarily automates coding processes using algorithms, reducing manual effort. Medical Coding Specialists manually review and assign codes, often requiring certifications. AI enhances efficiency, while specialists ensure accuracy and compliance. Both play vital roles in healthcare documentation and billing.

What are popular job titles related to Medical Coding Artificial Intelligence jobs in California?

For Medical Coding Artificial Intelligence jobs in California, the most frequently searched job titles are:

What job categories do people searching Medical Coding Artificial Intelligence jobs in California look for?

The top searched job categories for Medical Coding Artificial Intelligence jobs in California are:

What cities in California are hiring for Medical Coding Artificial Intelligence jobs?

Cities in California with the most Medical Coding Artificial Intelligence job openings:

Medical Coding Artificial Intelligence jobs near you
Infographic showing various Medical Coding Artificial Intelligence job openings in California as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution.

Artificial Intelligence Researcher

Verita AI

Santa Rosa, CA • On-site

Other

Posted 6 days ago

Key responsibilities

  • Work with clients to understand their models, goals, and performance gaps.

  • Design evaluations for generative, multimodal, reasoning, tool-use, and agentic AI systems.

  • Analyze model outputs and benchmark results to identify and quantify failure modes.

Job description

Location: San Francisco

Employment Type: Full-time

Work Model: In-person


About Verita AI

Verita AI works with leading AI companies to identify model gaps and build the human data needed to improve model performance. Verita AI operates a vetted expert network that connects specialized professionals with leading AI laboratories and human-data companies. The network comprises more than 5,000 experts across finance, medicine, law, engineering, music, and other professional domains.


We recently raised a $6 million seed round led by Kindred Ventures.


About the Role

We are hiring an Applied AI Researcher to work directly with clients on model evaluation and data strategy.


You will evaluate model performance, identify failure modes, and recommend the datasets, rubrics, expert workflows, and quality controls needed to address them. You will then work with our operations and engineering teams to turn these recommendations into scalable data programs.


What You’ll Do

  • Work with clients to understand their models, goals, and performance gaps.
  • Design evaluations for generative, multimodal, reasoning, tool-use, and agentic AI systems.
  • Analyze model outputs and benchmark results to identify and quantify failure modes.
  • Recommend data solutions such as supervised fine-tuning data, preference data, expert demonstrations, critiques, and evaluation datasets.
  • Write client proposals covering the methodology, data design, quality controls, staffing, deliverables, and expected impact.
  • Create annotation guidelines, scoring rubrics, gold-standard tasks, and evaluator-training programs.
  • Design pilot studies and measure whether data interventions improve model performance.
  • Build quality systems using calibration tasks, blind review, adjudication, and expert scoring.
  • Work with operations and engineering teams to launch and scale data pipelines.
  • Present findings and recommendations to clients.


What We’re Looking For

  • Experience in applied AI research, machine learning, model evaluation, or data-centric AI.
  • Experience evaluating foundation models or generative AI systems.
  • Strong understanding of benchmark design, human evaluation, rubric development, and statistical analysis.
  • Ability to translate model failures into practical data solutions.
  • Strong Python skills and experience working with model APIs and structured datasets.
  • Familiarity with supervised fine-tuning, preference optimization, RLHF/RLAIF, reward modeling, synthetic data, or LLM-as-a-judge evaluation.
  • Strong technical writing and client communication skills.
  • Ability to independently structure and execute ambiguous research projects.


Nice to Have

  • Experience at an AI lab, foundation-model company, AI data company, or post-training team.
  • Experience designing expert-data or human-evaluation programs.
  • Experience evaluating multimodal, coding, agentic, or tool-use systems.
  • Publications at conferences such as NeurIPS, ICML, ICLR, ACL, or EMNLP.
  • Previous client-facing research, consulting, solutions engineering, or forward-deployed experience.
  • Public research, code, benchmarks, or evaluation frameworks.


Please make sure you have any relevant work samples, including model evaluations, benchmarks, error analyses, research, technical writing, or code repositories.


Apply