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Medical Coding Artificial Intelligence Jobs (NOW HIRING)

Innovaccer Analytics

Medical Coding Specialist - I

$24 - $28/hr

The Healthcare Intelligence Cloud equips every stakeholder in the patient journey to turn ... The Medical Coder works closely with revenue cycle partners to prevent claim rejections, support ...

LS3002 GE Vernova Operations LLC

NY · On-site

$98 - $164/hr

Demonstrated ability to write Python code * Familiarity with GenAI packages including models from ... Benefits * medical, dental, vision, and prescription drug coverage * access to Health Coach from GE ...

Aston Carter

Medical Coder

Manhattan, NY · On-site

$75/hr

Experience in medical billing, medical ... coding, and healthcare operations. * Proficiency in using artificial intelligence and large ...

Aston Carter

Medical Coder

Manhattan, NY · On-site

$75/hr

Experience in medical billing, medical ... coding, and healthcare operations. * Proficiency in using artificial intelligence and large ...

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How much do medical coding artificial intelligence jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for medical coding artificial intelligence in the United States is $29.99, according to ZipRecruiter salary data. Most workers in this role earn between $24.76 and $34.38 per hour, depending on experience, location, and employer.

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.

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Medical Coding Artificial Intelligence jobs near you
Infographic showing various Medical Coding Artificial Intelligence job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 15% Part Time, and 6% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $62,377 per year, or $30 per hour.

Artificial Intelligence Software Engineer

10xTalents

Manhattan, NY • On-site, Remote

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Artificial Intelligence Software Engineer About the job Artificial Intelligence Software Engineer Artificial Intelligence Software Engineer - Hybrid/Remote - NYC No visa sponsorship available at this time. Our client an up and coming innovative AI start-up is seeking a highly skilled and innovative Artificial Intelligence Software Engineer to join their dynamic team. In this role, you will be responsible for designing, developing, and implementing AI algorithms and software solutions to solve complex problems across various domains. The ideal candidate will have a strong background in machine learning, deep learning, and software development, with a passion for pushing the boundaries of AI technology.

Responsibilities:

Collaborate with cross-functional teams to understand project requirements and develop AI-driven solutions tailored to specific applications. Design and implement machine learning algorithms and models for tasks such as classification, regression, clustering, and natural language processing.

Develop and optimize neural networks and deep learning architectures for tasks such as image recognition, speech recognition, and recommendation systems. Collect, preprocess, and analyze large datasets to train and evaluate AI models, ensuring robust performance and generalization. Implement scalable and efficient software solutions for deploying AI models in production environments, including cloud-based platforms and edge devices.

Collaborate with software engineers to integrate AI capabilities into existing software systems and develop AI-driven features and products. Research and evaluate emerging technologies and techniques in machine learning and AI, staying abreast of advancements in algorithms, frameworks, and tools. Document design specifications, implementation details, and best practices for internal and external stakeholders. Provide technical guidance and mentorship to junior engineers and contribute to the overall technical expertise of the team.

Requirements:

Bachelor's degree in Computer Science, Electrical Engineering, or related field. Master's or Ph.D. preferred. Proven experience in machine learning, deep learning, and AI software development, with a minimum of 3 years in a relevant role. Proficiency in programming languages such as Python, Java, or C++, and experience with AI frameworks such as TensorFlow, PyTorch, or scikit-learn. Strong understanding of machine learning algorithms, including supervised learning, unsupervised learning, and reinforcement learning.

Experience with deep learning techniques and architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformer models. Familiarity with software engineering best practices, including version control, testing, and code review. Excellent problem-solving skills and the ability to analyze complex technical challenges and propose innovative solutions.

Strong communication and collaboration skills, with the ability to work effectively in a multidisciplinary team environment. Experience with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes) is a plus.

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