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Healthcare Machine Learning Jobs in Ohio (NOW HIRING)

Pwc

Payer Healthcare Data Scientist, Manager

Toledo, OH · On-site

$99K - $232K/yr

... and machine learning techniques to large-scale claims, clinical, and member data to surface ... care and improve population health outcomes for our payer clients. As a Manager, you will lead ...

Pwc

Payer Healthcare Data Scientist, Manager

Cleveland, OH · On-site

$99K - $232K/yr

... and machine learning techniques to large-scale claims, clinical, and member data to surface ... care and improve population health outcomes for our payer clients. As a Manager, you will lead ...

A-TEK Inc.

Health IT Data Scientist

Continental, OH · Remote

$110K - $120K/yr

... healthcare decision-making across DHS Health IT initiatives. This is a remote position. US ... Develop predictive models and machine learning algorithms. * Perform statistical analyses on ...

Oakmont Education

Healthcare Instructor

Lakewood, OH · On-site

Periodically evaluates students learning and provides specific, accurate, and substantive feedback ... health-care program. The costs for the class will be covered by the school. * Certified as an ...

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Showing results 21-40

All JobsHealthcare Machine Learning JobsHealthcare Machine Learning Jobs in Ohio

Healthcare Machine Learning information

See Ohio salary details

$10.5K

$93.2K

$152.6K

How much do healthcare machine learning jobs pay per year?

As of Sep 7, 2026, the average yearly pay for healthcare machine learning in Ohio is $93,168.00, according to ZipRecruiter salary data. Most workers in this role earn between $20,900.00 and $152,100.00 per year, depending on experience, location, and employer.

What is a healthcare machine learning?

A Healthcare Machine Learning job involves developing and applying machine learning models to analyze medical data and improve healthcare outcomes. Professionals in this role work with electronic health records, medical imaging, genomics, and other healthcare data to assist in disease prediction, diagnosis, and personalized treatments. They collaborate with clinicians, data scientists, and engineers to ensure models are clinically relevant and ethically sound. Strong knowledge of machine learning, data preprocessing, and regulatory compliance (such as HIPAA) is essential.

What are the key skills and qualifications needed to thrive in healthcare machine learning?

To thrive in Healthcare Machine Learning, you need strong expertise in data science, machine learning algorithms, and biomedical informatics, often supported by an advanced degree in computer science, statistics, or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and healthcare data standards (like HL7 or FHIR) is highly beneficial, and certifications in data science or health informatics can provide an edge. Excellent problem-solving skills, attention to detail, and the ability to communicate complex technical concepts to diverse healthcare teams are valuable soft skills. These competencies are vital for developing robust, ethically sound machine learning solutions that improve clinical decision-making and patient outcomes.

What are some common challenges faced by professionals working in healthcare machine learning?

Professionals in Healthcare Machine Learning often encounter challenges such as navigating complex, unstructured, or incomplete healthcare data while ensuring strict compliance with privacy regulations like HIPAA. They must also bridge the gap between technical requirements and clinical needs, collaborating closely with medical professionals who may not have a technical background. Additionally, validating and interpreting machine learning models for real-world clinical use adds another layer of complexity, as solutions must be both accurate and explainable. Overcoming these challenges requires strong technical skills, effective teamwork, and a commitment to ethical, patient-centered solutions.

What does machine learning do in healthcare?

Healthcare machine learning involves developing algorithms that analyze medical data to assist in diagnosis, treatment planning, and predicting patient outcomes. Professionals in this field use tools like Python and TensorFlow, and often require knowledge of medical terminology and data privacy regulations to improve healthcare delivery.

What are popular job titles related to Healthcare Machine Learning jobs in Ohio?

For Healthcare Machine Learning jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Healthcare Machine Learning jobs in Ohio look for?

The top searched job categories for Healthcare Machine Learning jobs in Ohio are:

Healthcare Machine Learning jobs near you
Infographic showing various Healthcare Machine Learning job openings in Ohio as of August 2026, with employment types broken down into 1% Locum Tenens, 2% As Needed, 67% Full Time, 15% Part Time, 1% Temporary, and 14% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $93,168 per year, or $44.8 per hour.

AI Machine Learning Principal Engineer

Honda Dev. and Mfg. of Am.,LLC

Raymond, OH

$103K - $128K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 17 days ago

Job description

What Makes a Honda, is Who makes a Honda
Honda has a clear vision for the future, and it’s a joyful one.  We are looking for individuals with the skills, courage, persistence, and dreams that will help us reach our future-focused goals. At our core is innovation. Honda is constantly innovating and developing solutions to drive our business with record success.  We strive to be a company that serves as a source of “power” that supports people around the world who are trying to do things based on their own initiative and that helps people expand their own potential. To this end, Honda strives to realize “the joy and freedom of mobility” by developing new technologies and an innovative approach to achieve a “zero environmental footprint.”

We are looking for qualified individuals with diverse backgrounds, experiences, continuous improvement values, and a strong work ethic to join our team.

If your goals and values align with Honda’s, we want you to join our team to Bring the Future!

Job Purpose

Lead the design, development, and deployment of advanced AI and machine learning solutions supporting Honda’s automotive R&D initiatives, with a focus on production-grade AI for vehicle development, simulation, manufacturing quality, and digital twins—owning solutions end-to-end and mentoring engineers while partnering with CAE, CAD, manufacturing, and data platform teams.

Key Accountabilities
  • Lead development and validation of AI/ML solutions with measurable impact for automotive engineering - CAE, and manufacturing use cases.
  • Design and deploy AI surrogate models using Graph Convolutional Neural Networks (GCNNs) to augment/replace physics-based CAE.
  • Architect and deploy scalable cloud-based AI systems on AWS/Azure aligned with enterprise governance.
  • Own the full AI lifecycle: data ingestion, feature engineering, training, evaluation, deployment, and monitoring.
  • Implement MLOps and GenAIOps best practices (versioning, drift detection, CI/CD, traceability).
  • Develop and deploy agentic AI solutions for CAE in the cloud and deploy AI agents to execute/augment/monitor workflows.
  • Support ETL activities related to ADC data (CAE) structure.
  • Establish design standards, code quality, and documentation to support reuse and auditability.
  • Mentor and technically guide mid-level and junior engineers.
Qualifications, Experience, and Skills
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field, or equivalent experience.
  • 8+ years of experience developing and deploying ML/AI systems; 3+ years in production environments.

Other Job-Specific Skills    

  • Hands-on experience with graph neural networks (GCNNs, GNNs, GATs, MPNNs)
  • Advanced proficiency in Python; C++ or Java is a strong plus for automotive contexts
  • Deep expertise in ML frameworks (PyTorch, TensorFlow, scikit-learn)
  • Strong foundation in statistics, optimization, and numerical methods
  • Hands-on experience deploying AI solutions on AWS/Azure (e.g., Amazon Bedrock)
  • Experience with LangGraph / LangChain & Strands SDK. 
  • Experience with containers, pipelines, and MLOps tooling (Docker, MLflow, CI/CD)
  • Knowledge of model governance, compliance, and responsible AI frameworks 
  • CAE/physics-informed ML, surrogate modelling, or simulation experience (preferred).
  • Prior knowledge of automotive or related design engineering work is a plus.
Job Dimensions
Decisions Expected
Working Conditions
  • Work is primarily conducted at an office desk; hybrid (office/home) work may be available.
  • Occasional travel and overtime may be required based on project milestones.
  • Work in a cross-functional environment supporting engineering, simulation, and manufacturing stakeholders.

What differentiates Honda and makes us an employer of choice?

Total Rewards: 

  • Competitive Base Salary (pay will be based on several variables that include, but not limited to geographic location, work experience, etc.)
  • Regional Bonus (when applicable)
  • Manager Lease Car Program (No Cost - Car, Maintenance, and Insurance included)
  • Industry-leading Benefit Plans (Medical, Dental, Vision, Rx)
  • Paid time off, including vacation, holidays, shutdown
  • Company Paid Short-Term and Long-Term Disability 
  • 401K Plan with company match + additional contribution
  • Relocation assistance (if eligible)

Career Growth:

  • Advancement Opportunities
  • Career Mobility
  • Education Reimbursement for Continued learning
  • Training and Development Programs 

Additional Offerings:

  • Lifestyle Account
  • Childcare Reimbursement Account
  • Elder Care Support
  • Tuition Assistance & Student Loan Repayment
  • Wellbeing Program
  • Community Service and Engagement Programs
  • Product Programs

Honda is an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.

Apply