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Mlops Data Engineer Jobs in Baltimore, MD (NOW HIRING)

DPR Construction

MLOps Engineer

Baltimore, MD · On-site

DPR 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 ...

T Rowe Price

AI Data Engineer

Baltimore, MD · Hybrid

$113K - $136K/yr

Familiarity with MLOps, CI/CD pipelines, and model lifecycle management. * Industry certifications in cloud or data engineering technologies. * Knowledge of data privacy, compliance (e.g., GDPR), and ...

T. Rowe Price Associates, Inc.

AI Data Engineer

Baltimore, MD · Hybrid

$113K - $136K/yr

Familiarity with MLOps, CI/CD pipelines, and model lifecycle management. * Industry certifications in cloud or data engineering technologies. * Knowledge of data privacy, compliance (e.g., GDPR), and ...

Parsons

Senior Software Developer (MLOps)

Aberdeen, MD

$58.50 - $77.50/hr

Collaborate with data scientists and ML engineers to productionize models, including feature pipelines, inference services, and monitoring * Implement and maintain end-to-end MLOps workflows ...

eSimplicity

Data Engineer II

Columbia, MD · On-site

$93K - $100K/yr

Partnering with engineering, product, and data teams, this position provides technical leadership ... Knowledge of MLOps and LLMOps practices, including source control, CI/CD pipelines, automated ...

Cisive

Senior Engineer, Data and AI

Annapolis, MD · On-site

$120 - $180/hr

... data and AI engineering. They will be responsible for designing and implementing data ... MLOps/LLMOps: Experience deploying, monitoring, and maintaining models and AI systems in production ...

InterImage

AI Engineer

Annapolis Junction, MD · On-site

Deploy models into production environments using MLOps best practices Collaboration & Communication * Serve as a technical liaison across engineering, data, and mission stakeholders * Clearly ...

InterImage, Inc.

AI Engineer

Annapolis, MD · On-site

$100 - $130/hr

Deploy models into production environments using MLOps best practices Collaboration & Communication * Serve as a technical liaison across engineering, data, and mission stakeholders * Clearly ...

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All JobsMlops Data Engineer JobsMlops Data Engineer Jobs in Baltimore, MD

Mlops Data Engineer information

See Baltimore, MD salary details

$44.2K

$128.9K

$176.4K

How much do mlops data engineer jobs pay per year?

As of Aug 28, 2026, the average yearly pay for mlops data engineer in Baltimore, MD is $128,891.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,800.00 and $136,600.00 per year, depending on experience, location, and employer.

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

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

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What are popular job titles related to Mlops Data Engineer jobs in Baltimore, MD?

For Mlops Data Engineer jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Mlops Data Engineer jobs in Baltimore, MD look for?

The top searched job categories for Mlops Data Engineer jobs in Baltimore, MD are:

What cities near Baltimore, MD are hiring for Mlops Data Engineer jobs?

Cities near Baltimore, MD with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Baltimore, MD as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $128,891 per year, or $62 per hour.

MLOps Engineer

Baltimore, MD • On-site

DPR Construction
Construction • 10K+ employees

8.0

Company rating: 8.0 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

17th of 80 rated construction

People enjoy working here

Good employer

Recommended by students

Learn more about DPR Constructionexternal

Full-time

This job post has expired today. Applications are no longer accepted.

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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