1

Mlops Data Engineer Jobs in Raleigh, NC (NOW HIRING)

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 ...

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 ...

AI Data Engineer - Manager

Raleigh, NC · On-site

$111.30K - $133.70K/yr

AI Data Engineer - Manager Our Human Capital practice is at the forefront of transforming the ... Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and ...

AI Data Engineer - Senior Consultant

Raleigh, NC · Hybrid

$101.60K - $139.50K/yr

You will work with an AI Data Engineer (data ingestion, curation, governance, platform foundations ... Contribute to MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated ...

AI Data Engineer - Senior Consultant

Raleigh, NC · On-site

$103K - $140K/yr

... MLOps/LLMOps and production operations (versioning, reproducibility, CI/CD, automated testing ... Engineering, Statistics, Data Science) • 4+ years building and delivering LLM/GenAI solutions ...

... MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage ... Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to ...

Lead AI and Data Science Engineer - Manager

Raleigh, NC · On-site

$111.30K - $133.70K/yr

... MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage ... Data & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to ...

AI Engineer Senior Consultant

Raleigh, NC · Hybrid

$101.60K - $139.50K/yr

... and HR data domains. * 4+ years of experience operationalizing LLMOps/MLOps capabilities ... AI Engineer Senior Consultant Our Deloitte Human Capital team transforms technology platforms ...

Partner with engineering teams to align to MLOps and LLMOps expectations for deployment, monitoring ... Hands on experience as a lead data scientist, AI/ML engineer, data engineer or solution architect ...

Partner with engineering teams to align to MLOps and LLMOps expectations for deployment, monitoring ... Hands on experience as a lead data scientist, AI/ML engineer, data engineer or solution architect ...

... and HR data domains. * 4+ years of experience operationalizing LLMOps/MLOps capabilities ... AI Engineer III Position Summary Our Deloitte Human Capital team transforms technology platforms ...

... and HR data domains. * 2+ years of experience operationalizing LLMOps/MLOps capabilities ... AI Engineer Consultant Our Deloitte Human Capital team transforms technology platforms, drives ...

AI/ML Engineer

Raleigh, NC · Remote

$140K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference ... Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and ...

AI/ML Engineer

Raleigh, NC · Remote

$140K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference ... Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and ...

AI/ML Engineer

Durham, NC · Remote

$140K - $220K/yr

Develop and operationalize MLOps pipelines (MLflow, Kubeflow, DVC, or custom training/inference ... Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and ...

next page

Showing results 1-20

Mlops Data Engineer information

See Raleigh, NC salary details

$43.3K

$126.1K

$172.5K

How much do mlops data engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for mlops data engineer in Raleigh, NC is $126,095.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,300.00 and $133,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an MLOps Data Engineer, and why are they important?

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 are MLOps Data Engineers?

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 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.

What cities near Raleigh, NC are hiring for Mlops Data Engineer jobs? Cities near Raleigh, NC with the most Mlops Data Engineer job openings:
MLOps Engineer

Full-time

Posted 13 days ago


DPR Construction rating

7.8

Company rating: 7.8 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

23rd of 77 rated construction


Job description

Job Description
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 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 a MLOps Engineer to join our team and contribute to developing robust data solutions to support our Machine Learning, Data Science, Data Engineering and Software Engineering.
Position Overview
The MLOps Engineer will be instrumental in the design and implementation of scalable, cloud-native solutions to meet the growing needs of our Data & Development team. The successful candidate will demonstrate the ability to abstract complexity and create reusable, scalable patterns that accelerate development. The MLOps Engineer will design, build and support the infrastructure and systems that enable our teams to deliver reliable, high-impact data, workflows, and collaborating closely 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 practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms

  • Design and deploy containerized ML workloads, partnering with Infrastructure Engineering 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 with Infrastructure Engineering to automate infrastructure provisioning

  • Act as a technical point of contact for DevOps and MLOps 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 in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering

  • Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure

  • Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn

Required Skills
  • Experience with CI/CD processes and automation

  • Experience with Infrastructure as Code tools such as Terraform, Bicep

  • Proficiency in containerized application deployments and container orchestration - experience with Kubernetes, especially AKS would be a huge plus

  • Experience standing up and managing observability tools such as Datadog, Azure Monitor or Grafana for APM, LLM Ops and model performance monitoring

  • Experience deploying production-ready machine learning models

  • Experience with Model 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 at www.dpr.com/careers.

What DPR Construction employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom