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Mlops Jobs (NOW HIRING)

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 ...

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 ...

MLOps Engineer

Dallas, TX · On-site

$55.50 - $74/hr

Ability to design and implement MLOPs cloud solutions, considering scalability, security, and performance. o Experience: Practical firsthand experience with cloud MLOps and Data Analytics platforms ...

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 ...

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 ...

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 ...

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 ...

Experience building and maintaining MLOps/LLMOps platforms * Cloud expertise in Azure and/or Google Cloud Platform * CI/CD pipeline development and automation * Model deployment, monitoring, and ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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Mlops information

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.

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 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.
What cities are hiring for Mlops jobs? Cities with the most Mlops job openings:
What are the most commonly searched types of Mlops jobs? The most popular types of Mlops jobs are:
What states have the most Mlops jobs? States with the most job openings for Mlops jobs include:
MLOPS Engineer

MLOPS Engineer

Accord Technologies Inc.

Chicago, IL • On-site

Contractor

Posted 29 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