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Machine Learning Biomedical Engineer Jobs in Saint Augustine, FL

Machine Learning Operations Engineer

Jacksonville, FL · On-site +1

$47.50 - $65/hr

Learn more at Position Summary We are seeking an experienced Machine Learning Ops (MLOps) Engineer to architect, develop, and maintain the full lifecycle of data and model pipelines that power ...

New

Machine Learning Operations Engineer

Jacksonville, FL · On-site

$47.50 - $65/hr

Learn more at Position Summary We are seeking an experienced Machine Learning Ops (MLOps) Engineer to architect, develop, and maintain the full lifecycle of data and model pipelines that power ...

New

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Collaborate with data engineering teams to define data requirements, optimize data pipelines, and ensure availability of high-quality data for analytics and machine learning initiatives. * Ensure ...

Collaborate with data engineering teams to define data requirements, optimize data pipelines, and ensure availability of high-quality data for analytics and machine learning initiatives. * Ensure ...

Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization. * Communicate complex analytical ...

New

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Machine Learning Biomedical Engineer information

See Saint Augustine, FL salary details

$27.5K

$112.3K

$168.8K

How much do machine learning biomedical engineer jobs pay per year?

As of Aug 30, 2026, the average yearly pay for machine learning biomedical engineer in Saint Augustine, FL is $112,321.00, according to ZipRecruiter salary data. Most workers in this role earn between $88,500.00 and $135,200.00 per year, depending on experience, location, and employer.

What does a machine learning biomedical engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

How does a machine learning biomedical engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.

What are the key skills and qualifications needed to thrive as a machine learning biomedical engineer, and why are they important?

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What are popular job titles related to Machine Learning Biomedical Engineer jobs in Saint Augustine, FL?

For Machine Learning Biomedical Engineer jobs in Saint Augustine, FL, the most frequently searched job titles are:

What job categories do people searching Machine Learning Biomedical Engineer jobs in Saint Augustine, FL look for?

The top searched job categories for Machine Learning Biomedical Engineer jobs in Saint Augustine, FL are:

What cities near Saint Augustine, FL are hiring for Machine Learning Biomedical Engineer jobs?

Cities near Saint Augustine, FL with the most Machine Learning Biomedical Engineer job openings:

Infographic showing various Machine Learning Biomedical Engineer job openings in Saint Augustine, FL as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $112,321 per year, or $54 per hour.

Machine Learning Operations Engineer

Jacksonville, FL • On-site, Remote

$47.50 - $65/hr

Full-time

Posted 2 days ago

New


Job description

About Mosai

Mosai is the intelligent care coordination platform that brings together the fragmented pieces of healthcare into a clear, connected picture. Like a mosaic, our platform unites data, people, and processes so providers can make better decisions, coordinate care in real time, and deliver improved outcomes. With Mosai, home-based care organizations can thrive in value-based care while giving every patient the right care, in the right place, at the right time. Learn more at https://www.mosai.com/

Position Summary

We are seeking an experienced Machine Learning Ops (MLOps) Engineer to architect, develop, and maintain the full lifecycle of data and model pipelines that power training, inference, evaluation, and analytics workflows. This role is responsible for ensuring the reliability, scalability, and observability of all machine learning systems in production, including traditional ML models and modern LLM-based/MCP-orchestrated architectures. A key focus of this role in the near term is auditing and consolidating our existing pipelines and deployment processes. The ideal candidate is highly skilled in Python, Jupyter, Snowflake, and both Azure and AWS cloud environments, and thrives in environments requiring continuous monitoring, rapid issue diagnosis, and rigorous validation before deployment.

Job Duties

  • Design, build, and maintain scalable data pipelines supporting model training, inference, batch processing, and real-time analytics workflows.
  • Audit, refactor, and consolidate existing ML pipelines and deployment processes to eliminate technical debt, redundant workflows, and undocumented manual steps.
  • Audit, refactor, and consolidate existing ML pipelines and deployment processes to eliminate technical debt, redundant workflows, and undocumented manual steps.
  • Monitor and deploy and deploy production ML pipelines to identify anomalies, performance degradations, or failures related to data quality, logic defects, or infrastructure issues.
  • Execute rapid troubleshooting and root-cause analysis followed by timely remediation, validation, and full regression testing prior to redeployment.
  • Collaborate with Data Science, Engineering, and Product teams to operationalize machine learning models-including LLM-based and MCP-orchestrated systems-ensuring seamless integration into production environments.
  • Develop CI/CD workflows, model deployment strategies, and automated testing frameworks to support reliable, repeatable releases.
  • Implement and maintain observability tooling (logging, monitoring, alerting) to ensure high availability and traceability of ML systems.
  • Manage and optimize cloud infrastructure across Azure and AWS for compute, storage, orchestration, and security needs.
  • Create and maintain documentation, runbooks, and best practices for model operations and system maintenance.
  • Perform all other job-related duties as assigned.

Minimum Requirements

  • Bachelor's Degree in Computer Science, Engineering or equivalent work experience.
  • 5-7 years of combined experience in Data Engineering, MLOps, Machine Learning Engineering, or related fields.
  • Demonstrated experience operationalizing traditional ML models as well as LLM-based and MCP-orchestrated systems.
  • Strong working knowledge of both Azure and AWS cloud platforms, including compute orchestration, networking, and security best practices.
  • Experience with CI/CD tools, containerization (Docker), infrastructure-as-code, and ML pipeline frameworks.
  • Strong ability to diagnose and resolve pipeline failures, data anomalies, and complex system issues.

Advanced proficiency in Python, Jupyter, and common ML/analytics frameworks.

  • Hands-on experience with Snowflake or similar cloud data warehousing environment.
  • Excellent problem-solving skills, attention to detail, and a proactive, self-directed work ethic.
  • Strong communication skills and comfort working in fast-paced, cross-functional environments.

Work Environment


  • This role is preferred to be based in Nashville or Jacksonville, near Mosai's offices.

Physical Demands of Our Work Environment

  • This position uses a computer and other office equipment as needed to perform duties. The in-office noise level in the work environment is typical of that of an office. Frequent interruptions may be encountered throughout the workday.
  • The employee is required to either stand or sit, talk and hear frequently required to use repetitive keying or hand motions.
  • The physical demands are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Mosai is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status, If you are unable to submit an application because of a incompatible assistive technology or disability, please contact us at careers@mosai.com. We will make every effort to respond to your request for disability assistance as soon as possible.

Mosai is an E-verify employer. Your eligibility to work in the United States will be verified through the E-verify system if you apply and are selected for a position.