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Mlops Jobs (NOW HIRING)

Accord Technologies Inc.

MLOPS Engineer

Chicago, IL · On-site

MLOPS Engineer Location: Chicago, IL Duration: 12+ months Position type: W2 contract Required Skills f or the MLOps Engineer: - Bachelor's plus 9+ years of experience, Master ...

Siri InfoSolutions Inc

MLOPS Engineer

Malvern, PA · On-site

$50 - $60/hr

Role: MLOps Engineer Location: Malvern, PA / Raleigh, NC or USA Any LOcation (Onsite) Duration: Contract * Knowledge of MLOps platforms * Good experience with Sage Maker * Proven 8+ years of ...

Zortech Solutions

MLOps Engineer

Bellevue, WA · Remote

Job Title MLOps Engineer to work on AWS GovCloud Databricks Projected Start Date05-09-2025 Projected End Date10-31-2025 Position Type Contract Location : Bellevue, WA Remote Work100% Primary ...

DPR Construction

MLOps Engineer

Raleigh, NC · On-site

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 ...

Futran Tech Solutions Pvt. Ltd.

MLops Engineer

MLops engineer with GCP and Computer Vision exp Location: Remote (Dallas , TX) Job Details: Proficient in Python Programming >Understanding of MLOps, Model development lifecycle with experience in ...

Staffingine LLC

MLOps Engineer

Charlotte, NC · On-site

MLOps Engineer Job Location: Charlotte - North Carolina - USA Job Type: Contract * 4 to 6 years of strong experience with AWS Gov Cloud environments Export Control FedRAMP environments * Overall 8 to ...

DPR Construction

MLOps Engineer

Charlotte, NC · On-site

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 ...

DPR Construction

MLOps Engineer

Houston, TX

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 ...

Kapitus

MLOps Architect

Arlington, VA · On-site

$117K - $189K/yr

MLOps & GenAI Platform Architecture * Design and implement scalable ML and LLM infrastructure on AWS (SageMaker, EKS, S3, IAM, Lambda, Step Functions, CloudWatch). * Architect end-to-end ML and ...

DPR Construction

MLOps Engineer

Jacksonville, FL

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 ...

DPR Construction

MLOps Engineer

Richmond, VA · On-site

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 ...

DPR Construction

MLOps Engineer

East Brunswick, NJ

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 ...

DPR Construction

MLOps Engineer

Orlando, FL · On-site

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 ...

DPR Construction

MLOps Engineer

Nashville, TN

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 ...

Redolent, Inc.

Prinicipal MlOps Engineer

Sunnyvale, CA · On-site

Principal MLOps Engineer Location: Sunnyvale, CA Job Type: - Contract - 12+ Months Department: Data Science / Machine Learning About the Role We are seeking an experienced Principal MLOps Engineer to ...

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Mlops information

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$101.5K

$159.3K

$189.5K

How much do mlops jobs pay per year?

As of Jun 11, 2026, the average yearly pay for mlops in the United States is $159,286.00, according to ZipRecruiter salary data. Most workers in this role earn between $150,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What is the difference between Mlops vs Data Engineer?

AspectMlopsData Engineer
Primary FocusDeploying, managing, and monitoring machine learning models in productionBuilding and maintaining data pipelines and infrastructure for data processing
Skills & CertificationsMachine learning, DevOps, cloud platforms, scriptingSQL, ETL, data warehousing, programming
Work EnvironmentCollaborates with data scientists, software engineers, and DevOps teamsWorks with data analysts, data scientists, and software developers
Industry UsageAI/ML projects, production environments, cloud servicesData infrastructure, analytics, big data processing

While both Mlops and Data Engineers work closely with data and cloud technologies, Mlops specialists focus on deploying and maintaining machine learning models in production, ensuring their scalability and reliability. Data Engineers primarily build data pipelines and infrastructure to support data analysis and ML workflows. Understanding these distinctions helps organizations assign the right roles for their AI and data projects.

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

To thrive as an MLOps Engineer, you need a strong background in machine learning, software engineering, and DevOps principles, often supported by a degree in computer science or a related field. Proficiency with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (e.g., AWS, Azure, GCP), and ML frameworks is typically required, along with certifications in cloud or DevOps technologies. Strong problem-solving skills, collaboration, and communication abilities help MLOps professionals excel in cross-functional teams and manage complex workflows. These skills are vital for reliably deploying, monitoring, and scaling machine learning models in production environments, ensuring efficiency and robustness.

Is MLOps a good career path?

MLOps is a growing field that combines machine learning, software engineering, and operations to deploy and maintain AI models efficiently. It offers high demand for skills in cloud platforms, automation, and data management, making it a promising career choice for those interested in AI infrastructure. Professionals in MLOps often work with tools like Docker, Kubernetes, and CI/CD pipelines, and typically require a strong understanding of both machine learning and software development.

What are some common challenges faced by MLOps professionals when deploying machine learning models to production?

MLOps professionals often encounter challenges such as ensuring reproducibility of models, managing version control for both code and data, and maintaining model performance over time. Handling continuous integration and deployment (CI/CD) pipelines for ML models can be complex, especially when dealing with large datasets and evolving algorithms. Additionally, coordinating with data scientists, software engineers, and DevOps teams to streamline workflows and monitor models post-deployment are key responsibilities that require both technical expertise and strong collaboration skills.

What engineers make $500,000?

Senior machine learning operations (MLOps) engineers with extensive experience, specialized skills in cloud platforms, automation, and deployment often reach or exceed $500,000 annually in total compensation. High-level roles in tech companies or those with leadership responsibilities and advanced certifications tend to offer such salaries.

Which 3 jobs will survive AI?

For MLOps professionals, roles such as data scientists, machine learning engineers, and AI infrastructure engineers are expected to persist as AI adoption grows. These jobs require specialized skills in model development, deployment, and maintenance that complement automation. Continuous learning and expertise in tools like Kubernetes, cloud platforms, and version control are essential for long-term viability.

What is a $900,000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as senior machine learning engineer or AI director, often requiring advanced skills in data science, deep learning, and cloud platforms. These roles usually involve leadership, strategic planning, and extensive experience, and they may include bonuses or stock options that contribute to the total compensation. Such salaries are rare and generally found in large tech companies or specialized AI firms.

What are MLOps?

MLOps, short for Machine Learning Operations, is a set of practices that combines machine learning, DevOps, and data engineering to automate and streamline the deployment, monitoring, and maintenance of machine learning models in production. MLOps aims to improve collaboration between data scientists and operations teams, ensuring that models are robust, scalable, and easily updated. It covers the entire machine learning lifecycle, from data preparation to model training, deployment, and ongoing monitoring. By implementing MLOps, organizations can accelerate the development and deployment of reliable machine learning solutions.
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Mlops jobs near you

MLOPS Engineer

Accord Technologies Inc.

Chicago, IL • On-site

Contractor

Posted 9 days ago

Job description

Title: MLOPS Engineer
Location: Chicago, IL
Duration: 12+ months
Position type: W2 contract
 
 
Required Skills for the MLOps Engineer:
- Bachelor's plus 9+ years of experience, Master's plus 6+ years of experience
- Experience working with an object-oriented programming language (Python, Golang, Java, C/C++ etc.)
- Experience with MLOps frameworks like MLflow, Kubeflow, etc
- Proficiency in programming (Python, R, SQL)
- Ability to design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
- Strong understanding of DevOps principles and practices, CI/CD, etc. and tools (Git, GitHub, jFrog Artifactory, Azure DevOps, etc.)
- Experience with containerization technologies like Docker and Kubernetes
- Strong communication and collaboration skills
- Ability to help work with a team to create User Stories and Tasks out of higher-level requirements
 
Preferred Skills:
- Ability to create model inference systems with advanced deployment methods that integrate with other MLOps components like MLFlow
- Knowledge of inference systems like Seldon, Kubeflow, etc
- Knowledge of deploying applications and systems in Langfuse or Kubernetes using Helm and Helmfile
- Knowledge of infrastructure orchestration using CloudFormation or Terraform
- Exposure to observability tools (such as Evidently AI)
 
MLOps Engineer Overview:
The MLOps Platform Team works within the Enterprise Data and Analytics Organization driving the ability to work with Internal Teams to be able to support the full life-cycle of AI and machine learning development through to beyond production. Helping build a platform that enables data driven decisions across the enterprise, helping teams build high-value data and AI/ML products, and enable the operationalization and reliability of all models. We are searching for a driven and highly skilled MLOps Engineer to join our MLOps Platform team at ServiceNow. The role will build the MLOps Platform, build self-service ML Development tooling, and building platform adoption.
 
Responsibilities:
- Define scalable and secure architectures, frameworks and pipelines for building, deploying and diagnosing production ML applications
- Enable users & teams on the ML platform; troubleshoot and debug user issues; maintain user-friendly documentation and training
- Collaborate with internal stakeholders to build a comprehensive MLOps Platform
- Design and implement cloud solutions and build MLOps pipelines on cloud solutions (e.g., AWS)
- Develop standards and examples to accelerate the productivity of data science teams
- Run code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality, including data & concept drift
- Create way to automate the testing, validation, and deployment of data science models
- Provide best practices and execute POC for automated and efficient MLOps at scale
 
Education Requirements:
- Bachelor's degree or Master's degree