MLOps Engineer
Austin, TX · 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 ...
MLOps Engineer
Austin, TX · 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 ...
MLOps Engineer
Dallas, TX · 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 ...
MLOps Engineer
Dallas, TX · 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 ...
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 ...
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 ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
Prinicipal MlOps Engineer
Sunnyvale, CA · On-site
Optimize and manage cloud-based ML workloads using AWS, GCP, or Azure, ensuring cost-eJiciency and scalability. * Lead and mentor a team of MLOps engineers, collaborating closely with data scientists ...
Prinicipal MlOps Engineer
Sunnyvale, CA · On-site
Optimize and manage cloud-based ML workloads using AWS, GCP, or Azure, ensuring cost-eJiciency and scalability. * Lead and mentor a team of MLOps engineers, collaborating closely with data scientists ...
MLOps Engineer
$113K - $188K/yr
As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and ... Develop and manage model versioning, artifact management, and experiment tracking * Implement ...
MLOps Engineer
$113K - $188K/yr
As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and ... Develop and manage model versioning, artifact management, and experiment tracking * Implement ...
Data Architect -MLOps
$66.25 - $85.25/hr
Skilled in supporting and managing large, complex, and geographically distributed cloud environments. Strong background in risk assessment, control design, gap remediation, and impact analysis. MLOps ...
Data Architect -MLOps
$66.25 - $85.25/hr
Skilled in supporting and managing large, complex, and geographically distributed cloud environments. Strong background in risk assessment, control design, gap remediation, and impact analysis. MLOps ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
THE ROLE Senior Engineering Manager, MLOps We are seeking a Senior Engineering Manager, MLOps to join our growing team. The ideal candidate is a technical visionary with a proven track record of ...
THE ROLE Senior Engineering Manager, MLOps We are seeking a Senior Engineering Manager, MLOps to join our growing team. The ideal candidate is a technical visionary with a proven track record of ...
MLOps Platform Engineer
Reston, VA · On-site
MLOps Platform Engineer Location: Reston VA - In person interviews so need Local In EAST coast only ... Container & Kubernetes Workloads · Design and manage EKS workloads supporting containerized ML ...
Quick apply
MLOps Platform Engineer
Reston, VA · On-site
MLOps Platform Engineer Location: Reston VA - In person interviews so need Local In EAST coast only ... Container & Kubernetes Workloads · Design and manage EKS workloads supporting containerized ML ...
MLops Role
Dallas, TX · Remote
MLOps Capabilities • Experience with CI/CD pipelines tailored for ML workflows (e.g., GitHub ... management tools experience (e.g., MLflow or equivalent). • Logging, monitoring, and ...
Quick apply
MLops Role
Dallas, TX · Remote
MLOps Capabilities • Experience with CI/CD pipelines tailored for ML workflows (e.g., GitHub ... management tools experience (e.g., MLflow or equivalent). • Logging, monitoring, and ...
MLOps Engineer
Mclean, VA · On-site
$113K - $188K/yr
As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and ... Develop and manage model versioning, artifact management, and experiment tracking * Implement ...
MLOps Engineer
Mclean, VA · On-site
$113K - $188K/yr
As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and ... Develop and manage model versioning, artifact management, and experiment tracking * Implement ...
OR · On-site
$113K - $188K/yr
As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and ... Develop and manage model versioning, artifact management, and experiment tracking * Implement ...
OR · On-site
$113K - $188K/yr
As an MLOps Engineer, you will design, implement, and support the platforms, pipelines, and ... Develop and manage model versioning, artifact management, and experiment tracking * Implement ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
The MLOps Engineer will design, implement, and maintain end-to-end machine learning pipelines ... Deploy and manage machine learning models in production using tools like MLflow, Kubeflow, or AWS ...
MLOps Engineer
Wichita, KS · On-site
... management. * Implement and maintain containerized ML workloads in cloud-native environments ... Take ownership of MLOps practices within an applied research team, bringing structure ...
MLOps Engineer
Wichita, KS · On-site
... management. * Implement and maintain containerized ML workloads in cloud-native environments ... Take ownership of MLOps practices within an applied research team, bringing structure ...
Staff MLOps Engineer
Austin, TX · On-site
This is a hands-on technical leadership role, not a management position; you will be a primary ... Own the technical direction for the MLOps platform - define subsystem interfaces, drive ...
Staff MLOps Engineer
Austin, TX · On-site
This is a hands-on technical leadership role, not a management position; you will be a primary ... Own the technical direction for the MLOps platform - define subsystem interfaces, drive ...
MLOps Platform Engineer
Reston, VA · On-site
Key Responsibilities Platform Engineering & Operations · Engineer, manage, and support MLOps platform components across AWS and EKS-based environments. · Oversee deployment, configuration, and ...
Quick apply
MLOps Platform Engineer
Reston, VA · On-site
Key Responsibilities Platform Engineering & Operations · Engineer, manage, and support MLOps platform components across AWS and EKS-based environments. · Oversee deployment, configuration, and ...
Mlops Manager information
What is the difference between Mlops Manager vs Data Scientist?
| Aspect | Mlops Manager | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's/Master's in CS, Engineering, or related; certifications in cloud platforms or MLOps tools | Bachelor's/Master's in CS, Statistics, or related; certifications in data analysis or machine learning |
| Work Environment | Collaborates with engineering, DevOps, and data teams to deploy and maintain ML systems | Analyzes data, builds models, and provides insights to inform business decisions |
| Employer & Industry Usage | Tech companies, AI startups, enterprises implementing ML pipelines | Research 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 key skills and qualifications needed to thrive as an MLOps Manager, and why are they important?
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 are MLOps Managers?
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.
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What are the most commonly searched types of Mlops jobs? The most popular types of Mlops jobs are:
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DPR Construction rating
7.8
Based on 35 frontline employees who took The Breakroom Quiz
25th of 78 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.
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.
What DPR Construction employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About DPR Construction
Sourced by ZipRecruiter
Industry
Construction
Company size
10,000+ Employees
Headquarters location
Redwood City, CA, US
Year founded
1990