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Systems Architect 2, MLOps Engineer

Pay
Pay not listedSimilar roles state $166K–$240K
Work setting
Not stated
Employment
Full-time — employment source
Job Status: Full time Employee Type:
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting
  • Architect and implement infrastructure for machine learning and AI workloads

  • Build and maintain CI/CD pipelines for automated ML model deployment, monitoring and retraining

  • Design and manage hybrid cloud and on-premises environments with HIPAA and IRB compliance

  • Design and build APIs to serve and integrate ML models with other applications

  • Monitor deployed models for performance, drift and data integrity in real time

From the employer’s posting
Architect and implement infrastructure to support machine learning (ML) and artificial intelligence (AI) workloads across research, clinical, and operational domains
Build and maintain CI/CD pipelines using industry-standard tools (e.g., GitHub Actions, Jenkins, Azure DevOps) for automated ML model deployment, monitoring, and retraining
Design and manage hybrid cloud/on-premises environments to support high-performance computing, data privacy, and compliance requirements (e.g., HIPAA, IRB)
Design and implement robust APIs (e.g., RESTful, gRPC) to serve and integrate ML models with internal and external applications
Monitor system performance, model drift, and data integrity in real-time to maintain reliability and accuracy of deployed models
Apply at Umiami

Posting record

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Status in our records
Live
First seen by us
Oct 14, 202621 days ago
Recorded sightings
38
Last seen by us
Nov 4, 2026
Employer says posted
Oct 7, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 21

Similar jobs usually come down between day 6 and day 69.

From 4,301 similar postings that came down. Coming down is not always a hire.

Umiami is hiring

17 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring at a steady pace
  • Takes jobs down at a usual pace
  • 6% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • Azure
  • Docker
  • Kubernetes
  • MLflow
  • Terraform
  • Airflow
  • PyTorch
  • TensorFlow
Where the posting names them
- Architect and implement infrastructure to support machine learning (ML) and artificial intelligence (AI) workloads across research, clinical, and operational domains - Apply strong proficiency in Python and machine learning frameworks to build a platform that ensures reproducibility and scalability of advanced ML/AI solutions - Utilize deep experience with containerization, orchestration, and infrastructure-as-code to enable scalable and reproducible deployments of ML/AI workloads
- Experience with high-performance computing (HPC) or GPU-based workloads preferred - Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). - Strong proficiency with containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, ARM templates)
- Utilize deep experience with containerization, orchestration, and infrastructure-as-code to enable scalable and reproducible deployments of ML/AI workloads - Build and maintain CI/CD pipelines using industry-standard tools (e.g., GitHub Actions, Jenkins, Azure DevOps) for automated ML model deployment, monitoring, and retraining - Design and manage hybrid cloud/on-premises environments to support high-performance computing, data privacy, and compliance requirements (e.g., HIPAA, IRB)
- Minimum 8 years' experience in systems architecture, DevOps, or MLOps - Experience with hybrid cloud/on-prem environments, Azure preferred - Experience deploying and maintaining production workloads
- Strong proficiency with containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, ARM templates) - Proficiency with CI/CD tools (e.g., GitHub Actions, Jenkins, Azure DevOps) - Familiarity with ML lifecycle tools (e.g., MLflow, DVC, Airflow)
- Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). - Strong proficiency with containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, ARM templates) - Proficiency with CI/CD tools (e.g., GitHub Actions, Jenkins, Azure DevOps)
- Proficiency with CI/CD tools (e.g., GitHub Actions, Jenkins, Azure DevOps) - Familiarity with ML lifecycle tools (e.g., MLflow, DVC, Airflow) - Familiarity with data integration standards and protocols, particularly those used in healthcare, such as APIs, FHIR, HL7, and DICOM

Your next step

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Current Employees:

If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how to apply for a faculty or staff position, please review this tip sheet.

The UHealth-University of Miami Health System Information Technology & Systems Department has an opportunity for a full-time Systems Architect 2, MLOps Engineer.


The Systems Architect 2, MLOps Engineer is responsible for the independent design, development, and deployment of clinical applications and technologies. The architect defines system solutions based on user/client needs, cost, and required integration with existing applications, systems, or platforms. This employee also researches, identifies, selects, and tests technology products required for solution delivery. Establishes, implements, and documents technology integration or migration strategies. The employee must have the ability to proactively identify needs within the organization and, using expert technical and industry knowledge, design and build new solutions in support of organizational goals.


Core Responsibilities:

  • Engineers new workflows or optimize existing business processes that supersede existing standards set in place internally or by vendors utilizing expert knowledge crossing multiple clinical applications and operational areas.
  • Leads projects associated with application implementation and execution of high complexity and larger impact. Applies project management methodology and utilizes standard project management for software in development and maintenance of project plans.
  • Functions as an independent project lead or provides oversight for project manager and/or business analyst on assigned projects and recognize/ minimize business value lost during project/program execution.
  • Performs proactive analysis on current systems and technology in order to recommend potential changes or enhancements that will assist in adhering to organization's strategic vision and improve operational workflows as well as patient and end user experience.
  • Identifies product and customization requirements to effectively address necessary product configuration, while working within project scope and time line.
  • Serves as mentor to senior analysts and is proficient and/or certified in numerous applications.
  • Holds a comprehensive working knowledge and understands healthcare operational processes and job functions pertaining to assigned UHealth IT clinical applications and solutions.
  • Possesses expert knowledge of third party partnerships, experience with managing vendor relationships, and contract negotiations.
  • Provides support to the team in analyzing, resolving, and escalating complex integration problems encountered by the team during system implementations and upgrades.
  • Implement projects that are ahead of industry/peer trends. Thinks out of the box and follows the marking curve to stay on the forefront of Healthcare technology. Designs new solutions.
  • Participates in new hire orientation by providing the clinical application support in the work area required for the job role.
  • Collaborates with clinic leadership to develop or improve operational processes, polices, and procedures.
  • Participates in all clinical operations meetings to assess user feedback, gather future requirements for modifications, and provide a status on competency, adoption, and utilization rates.
  • Facilitates knowledge transfer of the technology-enabled user workflows and best practice use of applications.
  • Adheres to University and unit-level policies and procedures and safeguards University assets. 

Department Specific Functions:

  • Architect and implement infrastructure to support machine learning (ML) and artificial intelligence (AI) workloads across research, clinical, and operational domains
  • Apply strong proficiency in Python and machine learning frameworks to build a platform that ensures reproducibility and scalability of advanced ML/AI solutions
  • Utilize deep experience with containerization, orchestration, and infrastructure-as-code to enable scalable and reproducible deployments of ML/AI workloads
  • Build and maintain CI/CD pipelines using industry-standard tools (e.g., GitHub Actions, Jenkins, Azure DevOps) for automated ML model deployment, monitoring, and retraining
  • Design and manage hybrid cloud/on-premises environments to support high-performance computing, data privacy, and compliance requirements (e.g., HIPAA, IRB)
  • Collaborate with data scientists, IT teams, and clinical stakeholders to translate ML/AI models into production-ready services integrated with clinical, research, and administrative systems
  • Implement frameworks for model governance, versioning, and auditability to ensure responsible and transparent AI practices, and integrate tools to streamline MLOps workflows
  • Design and implement robust APIs (e.g., RESTful, gRPC) to serve and integrate ML models with internal and external applications
  • Monitor system performance, model drift, and data integrity in real-time to maintain reliability and accuracy of deployed models
  • Apply a strong knowledge of clinical data standards (e.g., FHIR, OMOP, DICOM) to solution design and implementation

 

This list of duties and responsibilities is not intended to be all-inclusive and may be expanded to include other duties or responsibilities as necessary. 

 

CORE QUALIFICATIONS:

  • Bachelor's Degree in relevant field
  • Epic or Healthcare EMR – Certification preferred
  • Minimum 8 years' experience in systems architecture, DevOps, or MLOps
  • Experience with hybrid cloud/on-prem environments, Azure preferred
  • Experience deploying and maintaining production workloads
  • Major systems development and implementation experience
  • Experience in healthcare or academic settings preferred
  • Experience mentoring and leading data teams, system engineering teams, or software engineering teams preferred
  • Experience with high-performance computing (HPC) or GPU-based workloads preferred
  • Strong proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch).
  • Strong proficiency with containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform, ARM templates)
  • Proficiency with CI/CD tools (e.g., GitHub Actions, Jenkins, Azure DevOps)
  • Familiarity with ML lifecycle tools (e.g., MLflow, DVC, Airflow)
  • Familiarity with data integration standards and protocols, particularly those used in healthcare, such as APIs, FHIR, HL7, and DICOM
  • Understanding of responsible AI practices and model governance frameworks
  • Understanding of data privacy, security, and compliance in regulated environments
  • Demonstrated knowledge of change control and project management
  • Excellent interpersonal skills and ability to communicate ideas and problem solutions
  • Works well independently and as part of a team
  • Knowledge of research compliance preferred

Any appropriate combination of relevant education, experience and/or certifications may be considered.

#LI-AS1



The University of Miami offers competitive salaries and a comprehensive benefits package including medical, dental, tuition remission and more.

UHealth-University of Miami Health System, South Florida's only university-based health system, provides leading-edge patient care powered by the ground breaking research and medical education at the Miller School of Medicine. As an academic medical center, we are proud to serve South Florida, Latin America and the Caribbean. Our physicians represent more than 100 specialties and sub-specialties, and have more than one million patient encounters each year. Our tradition of excellence has earned worldwide recognition for outstanding teaching, research and patient care. We're the challenge you've been looking for.

The University of Miami is an Equal Opportunity Employer. Applicants and employees are protected from discrimination based on certain categories protected by Federal law.

Job Status:

Full time

Employee Type:

Staff
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Location & working pattern

Miami, FL

- Build and maintain CI/CD pipelines using industry-standard tools (e.g., GitHub Actions, Jenkins, Azure DevOps) for automated ML model deployment, monitoring, and retraining - Design and manage hybrid cloud/on-premises environments to support high-performance computing, data privacy, and compliance requirements (e.g., HIPAA, IRB) - Collaborate with data scientists, IT teams, and clinical stakeholders to translate ML/AI models into production-ready services integrated with clinical, research, and administrative systems
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- Minimum 8 years' experience in systems architecture, DevOps, or MLOps - Experience with hybrid cloud/on-prem environments, Azure preferred - Experience deploying and maintaining production workloads
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