

Jobs via Dice
MLOps Engineer W2 Contract
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer on a long-term W2 contract in Chicago, IL (hybrid). Requires a Bachelor's/Master's degree, 5+ years of experience, proficiency in Python and MLOps frameworks, and strong DevOps knowledge.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
June 3, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Hybrid
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Chicago, IL
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🧠 - Skills detailed
#C++ #AWS (Amazon Web Services) #Java #Golang #SQL (Structured Query Language) #Deployment #Programming #Docker #Azure DevOps #Monitoring #Observability #Python #Scala #R #Stories #Terraform #Azure #Cloud #MLflow #Documentation #Artifactory #Kubernetes #Data Science #ML (Machine Learning) #DevOps #GitHub #AI (Artificial Intelligence) #GIT
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Keen Technology Solutions LLC, is seeking the following. Apply via Dice today!
MLOps Engineer
Chicago, IL, USA (hybrid)
Long term W2 contract
Education Requirements:
• Bachelor's degree or Master's degree Required Skills for the MLOps Engineer:
• Bachelor's plus 5+ years of experience, Master's plus 3+ 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
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Keen Technology Solutions LLC, is seeking the following. Apply via Dice today!
MLOps Engineer
Chicago, IL, USA (hybrid)
Long term W2 contract
Education Requirements:
• Bachelor's degree or Master's degree Required Skills for the MLOps Engineer:
• Bachelor's plus 5+ years of experience, Master's plus 3+ 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






