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Mlops Manager Jobs in Florida (NOW HIRING)

DPR Construction

MLOps Engineer

Orlando, FL

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Jacksonville, FL · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Tampa, FL · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Fort Lauderdale, FL · On-site

MLOps Engineer DPR is a leading construction company committed to delivering high-quality ... Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ...

DPR Construction

MLOps Engineer

Orlando, FL · On-site

... and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly ... MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive ...

Parsons

$103K - $181K/yr

Build, configure, and manage large-scale development and test environments to support robust ... Familiarity with MLOps frameworks and model registries (e.g., MLflow, Kubeflow). * Knowledge of ...

eTeam, Inc.

Senior MLOps Technical Lead

Sunrise, FL · On-site

CCaaS -- Senior MLOps Technical Lead 1. 8+ years of commercial software development experience. 2. ... management, ensuring scalable, secure, and compliant contact center operations. 6. Have experience ...

New

LTM

MLOpsEngineer

Tampa, FL · On-site

... MLOps best practices and tools Drive continuous improvement initiatives to enhance ML operational efficiency and scalability Coordinate with infrastructure and DevOps teams to provision and manage ML ...

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Mlops Manager information

What is an MLOps manager?

MLOps Managers are professionals responsible for overseeing the deployment, operation, and scaling of machine learning models in production environments. They coordinate teams to ensure seamless collaboration between data scientists, engineers, and IT staff, facilitating the automation of machine learning workflows. Their role involves managing infrastructure, optimizing processes for model monitoring and maintenance, and ensuring compliance with organizational and industry standards. MLOps Managers play a key role in bridging the gap between model development and operationalization, ensuring that machine learning solutions are reliable, reproducible, and scalable.

What are the key skills and qualifications needed to thrive as an MLOps manager?

To thrive as an MLOps Manager, you need expertise in machine learning, software engineering, and DevOps practices, often backed by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, Azure, GCP), and certifications such as AWS Certified Machine Learning or Google Cloud Professional ML Engineer are highly beneficial. Strong leadership, problem-solving, and cross-functional communication skills help manage teams and bridge the gap between data science and IT operations. These abilities are crucial for ensuring reliable, scalable, and efficient deployment of machine learning solutions in production environments.

What are some common challenges an MLOps manager faces when integrating machine learning models into production environments?

MLOps Managers often encounter challenges such as ensuring seamless collaboration between data science and engineering teams, managing model versioning, and maintaining reliable deployment pipelines. Balancing rapid experimentation with the need for robust, scalable, and secure production systems can be complex. Additionally, monitoring model performance post-deployment and handling data drift or model degradation are ongoing responsibilities. Effective communication and establishing standardized processes are key to overcoming these challenges and ensuring successful model operations.

What is the difference between Mlops Manager vs Data Scientist?

AspectMlops ManagerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; certifications in cloud platforms or MLOps toolsBachelor's/Master's in CS, Statistics, or related; certifications in data analysis or machine learning
Work EnvironmentCollaborates with engineering, DevOps, and data teams to deploy and maintain ML systemsAnalyzes data, builds models, and provides insights to inform business decisions
Employer & Industry UsageTech companies, AI startups, enterprises implementing ML pipelinesResearch institutions, tech firms, finance, healthcare, and marketing sectors

The Mlops Manager focuses on deploying, maintaining, and optimizing machine learning systems within an organization, working closely with engineering and DevOps teams. In contrast, a Data Scientist primarily analyzes data, develops models, and provides insights. While both roles require knowledge of machine learning, the Mlops Manager emphasizes operationalizing ML solutions, whereas the Data Scientist emphasizes data analysis and modeling.

What are the most commonly searched types of Mlops jobs in Florida?

The most popular types of Mlops jobs in Florida are:

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For Mlops Manager jobs in Florida, the most frequently searched job titles are:

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The top searched job categories for Mlops Manager jobs in Florida are:

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Cities in Florida with the most Mlops Manager job openings:

Mlops Manager jobs near you

MLOps Engineer

DPR Construction

Orlando, FL

Full-time

Re-posted 23 days ago

DPR Construction rating

8.0

Company rating: 8.0 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

17th of 80 rated construction

Job description

Job DescriptionDPR is looking for an experienced Data and MLOps Engineer to join our Data and AI team and work closely with the Data Platform, BI and Enterprise architecture teams to influence the technical direction of DPR's AI initiatives.
You will work closely with cross-functional teams, including business stakeholders, data engineers, and technical leads, to ensure alignment between business needs and data architecture and define data models for specific focus areas.

MLOps Engineer

DPR is a leading construction company committed to delivering high-quality, innovative projects. Our team integrates cutting-edge technologies into the construction process to streamline operations, enhance decision-making, and drive efficiency at all levels. We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering.

Position Overview

TheMLOps Engineerwill be instrumental inthe designand implementation of scalable, cloud-nativesolutions to meet the growing needs of ourData & Developmentteam.Thesuccessful candidatewill demonstrate the abilitytoabstract complexity andcreatereusable, scalable patternsthat accelerate development.The MLOps Engineerwilldesign, build and support the infrastructureand systemsthat enable our teams to deliver reliable, high-impactdata,workflows, and collaboratingclosely with data engineers, software developers, data scientists and product teams.

Responsibilities

  • Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning

  • Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection

  • Standardize observability practicesacross AI/ML and other development teamsincluding logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms

  • Design and deploy containerized MLworkloads,partnering withInfrastructureEngineering for cluster provisioning and governance

  • Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows

  • Implement AI-driven data validation, schema drift detection, and metadata management.

  • Establish governance frameworks for AI systems, including bias detection, explainability, and auditability

  • Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention

  • Collaborate withInfrastructureEngineering toautomate infrastructure provisioning

  • Act as a technical point of contact forDevOps andMLOps practices,developing reusable patterns, documentation, and proof-of-concepts to drive adoption

Qualifications

  • Bachelor's degree in Computer Science,Data Science,Information Systems, or a related field

  • 5+years of experience inDevOps, MLOps,Data Engineering,Software Engineeringor Site Reliability Engineering

  • Strong understanding of cloudinfrastructure and experience working with at least one major cloudprovider, preferably Azure

  • Proficiencyinat least one objected-oriented programming language, preferably pythonwith hands-on experience inml frameworks like TensorFlow, PyTorch or Scikit-learn

Required Skills

  • Experience with CI/CD processes and automation

  • Experience withInfrastructure as Codetoolssuch as Terraform,Bicep

  • Proficiencyincontainerized application deploymentsand container orchestration- experience with Kubernetes, especially AKS would be a huge plus

  • Experiencestanding up and managingobservability tools such as Datadog, Azure Monitor or GrafanaforAPM, LLM Opsand model performance monitoring

  • Experiencedeploying production-ready machine learning models

  • Experience withModel explainability (SHAP, LIME)or similar

  • Experience with cloud cost management and practices (e.g., Azure Cost Management, chargeback/show back models).

Nice to Have

  • Experience in Azure, particularly AKS,ACR, ARM,App Service, Azure Machine Learning and AI Foundry, Azure Monitor

  • Familiarity with semantic search, retrieval-augmented generation (RAG), or embedding pipelines

  • Exposure to managing and monitoring ML workloads that support generative AI or advanced analytics use cases

  • Proficiency with Snowflake

  • Experience with workflow orchestration platforms such as Apache Airflow, Argo Workflow, Prefect, etc.

DPR Construction is a forward-thinking, self-performing general contractor specializing in technically complex and sustainable projects for the advanced technology, life sciences, healthcare, higher education and commercial markets. Founded in 1990, DPR is a great story of entrepreneurial success as a private, employee-owned company that has grown into a multi-billion-dollar family of companies with offices around the world.

Working at DPR, you'll have the chance to try new things, explore unique paths and shape your future. Here, we build opportunity together-by harnessing our talents, enabling curiosity and pursuing our collective ambition to make the best ideas happen. We are proud to be recognized as a great place to work by our talented teammates and leading news organizations like U.S. News and World Report, Forbes, Fast Company and Newsweek.

Explore our open opportunities atwww.dpr.com/careers.

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