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 ...
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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 ...
MLOps Engineer
Dallas, TX · On-site
MLOps Engineer Location: Grapevine, TX & Dallas, TX - (Hybrid) Duration: 6+ Months Contract Key Responsibilities MLOps Lifecycle Ownership Own the full ML lifecycle: data ingestion, model training ...
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MLOps Engineer
Dallas, TX · On-site
MLOps Engineer Location: Grapevine, TX & Dallas, TX - (Hybrid) Duration: 6+ Months Contract Key Responsibilities MLOps Lifecycle Ownership Own the full ML lifecycle: data ingestion, model training ...
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 ...
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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 MLOps Engineer
Austin, TX · On-site
$140 - $190/hr
Join our ML Infrastructure team as an MLOps Engineer where you'll build the pipelines and platforms that deploy, monitor, and scale ML models from research to production. You'll bridge the gap ...
MLOps Engineer MLOps Engineer
Austin, TX · On-site
$140 - $190/hr
Join our ML Infrastructure team as an MLOps Engineer where you'll build the pipelines and platforms that deploy, monitor, and scale ML models from research to production. You'll bridge the gap ...
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 ...
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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 ...
MLOps Architect
$66.25 - $87/hr
Info Way Solutions is seeking a Senior MLOps Architect responsible for architecting and implementing scalable MLOps solutions. The role involves collaboration with data scientists and software ...
MLOps Architect
$66.25 - $87/hr
Info Way Solutions is seeking a Senior MLOps Architect responsible for architecting and implementing scalable MLOps solutions. The role involves collaboration with data scientists and software ...
MLOps Lead
New York, NY · On-site
$112K - $147K/yr
Senior MLOps Engineer Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices ...
MLOps Lead
New York, NY · On-site
$112K - $147K/yr
Senior MLOps Engineer Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices ...
JB061761 - MLOps Engineer
Grapevine, TX · On-site
$80/hr
MLOps Engineer Duration: 6 months+, possible extension Rate: $80/hr+, depending on experience Description We are seeking a highly skilled MLOps Engineer to support the IRAS (Item Recognition as a ...
JB061761 - MLOps Engineer
Grapevine, TX · On-site
$80/hr
MLOps Engineer Duration: 6 months+, possible extension Rate: $80/hr+, depending on experience Description We are seeking a highly skilled MLOps Engineer to support the IRAS (Item Recognition as a ...
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 ...
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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 ...
MLOps Engineer
Mclean, VA · On-site
MLOps Engineer Hybrid McLean, VA 12 months Interview Process: - Round 1: 30-minute job-fit interview - Round 2: 1-hour technical coding assessment interview (for candidates who pass job-fit) Must ...
MLOps Engineer
Mclean, VA · On-site
MLOps Engineer Hybrid McLean, VA 12 months Interview Process: - Round 1: 30-minute job-fit interview - Round 2: 1-hour technical coding assessment interview (for candidates who pass job-fit) Must ...
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 ...
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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 ...
NY · On-site
$120 - $160/hr
They need a senior MLOps engineer to build end‑to‑end ML pipelines in the cloud, automate model training and deployment, and ensure production ML systems are monitored, reliable, and scalable.
NY · On-site
$120 - $160/hr
They need a senior MLOps engineer to build end‑to‑end ML pipelines in the cloud, automate model training and deployment, and ensure production ML systems are monitored, reliable, and scalable.
MLOps Engineer
Portland, OR · On-site
Key Responsibilities • Design, build, and maintain end-to-end MLOps pipelines for model training, testing, deployment, and monitoring. • Automate ML workflows using CI/CD best practices. • ...
MLOps Engineer
Portland, OR · On-site
Key Responsibilities • Design, build, and maintain end-to-end MLOps pipelines for model training, testing, deployment, and monitoring. • Automate ML workflows using CI/CD best practices. • ...
MLOps Engineer
Austin, TX · On-site
Our client is looking MLOps Engineer project Austin, TX (Onsite) below is the detailed requirements. Job Title : MLOps Engineer Location : Austin, TX (Onsite) Duration : Long term * Bachelor's degree ...
MLOps Engineer
Austin, TX · On-site
Our client is looking MLOps Engineer project Austin, TX (Onsite) below is the detailed requirements. Job Title : MLOps Engineer Location : Austin, TX (Onsite) Duration : Long term * Bachelor's degree ...
MLOPs Engineer
Miami, FL · On-site
MLOPs Engineer Location: Hybrid Role (South Florida Preferred) Duration: 6+ Months (Must be able to convert FTE WITHOUT SPONSORSHIP) Required Skills: * 8+ years of Machine Learning Engineering or ...
MLOPs Engineer
Miami, FL · On-site
MLOPs Engineer Location: Hybrid Role (South Florida Preferred) Duration: 6+ Months (Must be able to convert FTE WITHOUT SPONSORSHIP) Required Skills: * 8+ years of Machine Learning Engineering or ...
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 ...
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 ...
MLOps Engineer
Arlington, VA · On-site
MLOps Engineer BizFirst is assisting our client with the hiring of an MLOps Engineer to build and operate the infrastructure, tooling, and processes that keep machine learning models running reliably ...
New
MLOps Engineer
Arlington, VA · On-site
MLOps Engineer BizFirst is assisting our client with the hiring of an MLOps Engineer to build and operate the infrastructure, tooling, and processes that keep machine learning models running reliably ...
New
Senior MLOps / LLMOps Engineer
Milpitas, CA · On-site
$119K - $163K/yr
Senior MLOps / LLMOps Engineer Location : Milpitas 4 days onsite contracts We are looking for a Senior MLOps / LLMOps Engineer to help standardize and enhance enterprise ML and GenAI deployment ...
Senior MLOps / LLMOps Engineer
Milpitas, CA · On-site
$119K - $163K/yr
Senior MLOps / LLMOps Engineer Location : Milpitas 4 days onsite contracts We are looking for a Senior MLOps / LLMOps Engineer to help standardize and enhance enterprise ML and GenAI deployment ...
MLOps Engineer
Arlington, VA · On-site
MLOps Engineer BizFirst is assisting our client with the hiring of an MLOps Engineer to build and operate the infrastructure, tooling, and processes that keep machine learning models running reliably ...
New
MLOps Engineer
Arlington, VA · On-site
MLOps Engineer BizFirst is assisting our client with the hiring of an MLOps Engineer to build and operate the infrastructure, tooling, and processes that keep machine learning models running reliably ...
New
MLOps Engineer
$115K - $150K/yr
We are seeking a MLOps Engineer to design, build, and support the infrastructure, tooling, and automation that enable scalable and reliable machine learning systems across our client engagements.
MLOps Engineer
$115K - $150K/yr
We are seeking a MLOps Engineer to design, build, and support the infrastructure, tooling, and automation that enable scalable and reliable machine learning systems across our client engagements.
Mlops information
What is 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 are the key skills and qualifications needed to thrive as an MLOps engineer?
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 is the difference between Mlops vs Data Engineer?
| Aspect | Mlops | Data Engineer |
|---|---|---|
| Primary Focus | Deploying, managing, and monitoring machine learning models in production | Building and maintaining data pipelines and infrastructure for data processing |
| Skills & Certifications | Machine learning, DevOps, cloud platforms, scripting | SQL, ETL, data warehousing, programming |
| Work Environment | Collaborates with data scientists, software engineers, and DevOps teams | Works with data analysts, data scientists, and software developers |
| Industry Usage | AI/ML projects, production environments, cloud services | Data 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.
Is MLOps in demand?
MLOps is a rapidly growing field as organizations increasingly adopt machine learning models in production. Professionals with skills in cloud platforms, automation, and tools like Kubernetes and Docker are highly sought after, reflecting strong industry demand for MLOps expertise.
Is MLOps outdated?
MLOps is an evolving field focused on deploying and managing machine learning models efficiently. It remains highly relevant as organizations increasingly adopt AI solutions, with skills in automation, cloud platforms, and monitoring tools in demand. Staying current with new tools and best practices is essential for MLOps professionals.
What is the average salary in MLOps?
The average salary for MLOps engineers typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Professionals with skills in cloud platforms, automation, and machine learning deployment tend to earn higher salaries.
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Job description
Title: MLOPS Engineer
Location: Chicago, IL
Duration: 12+ months
Position type: W2 contract
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
- 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)
- 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.
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
- 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
- Bachelor's degree or Master's degree
About Accord Technologies
Sourced by ZipRecruiter
Industry
It services
Company size
51 - 200 Employees
Headquarters location
Sheridan, WY, US