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MLOPs Engineer - Scottsdale AZ (100% Onsite)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Engineer in Scottsdale, AZ (100% onsite) with a contract duration of over 6 months. Key skills include Python, ML frameworks (TensorFlow, PyTorch), MLOps tools (MLflow, Kubeflow), and AWS experience.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 10, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Arizona, United States
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🧠 - Skills detailed
#Data Ingestion #TensorFlow #Cloud #Compliance #Scala #"ETL (Extract #Transform #Load)" #AWS (Amazon Web Services) #Model Deployment #PyTorch #MLflow #GitLab #SageMaker #Data Pipeline #Python #Security #ML (Machine Learning) #Data Science #Data Engineering #Azure #Deployment #GitHub #Airflow #Programming #Jenkins #Automation #Monitoring
Role description
One of our clients is currently hiring for the position of MLOps Engineer Please find the job details below. If you are interested, kindly share your most recent resume at []
Role : MLOps Engineer
Location : Scottsdale AZ (100% Onsite)
Hire Type : Contract / Full time
Role Overview
We are looking for a skilled MLOps Engineer to design, deploy, and manage scalable machine learning pipelines in production. The role focuses on enabling seamless integration of ML models into enterprise systems with reliability, automation, and governance.
Key Responsibilities
• Design and implement end-to-end ML pipelines from data ingestion to model deployment
• Build and manage CI/CD pipelines for ML models (training, testing, deployment)
• Automate model monitoring, retraining, and performance optimization
• Collaborate with Data Scientists and Data Engineers for productionizing ML models
• Ensure scalability, reliability, and security of ML systems
• Manage model versioning, experiment tracking, and lifecycle management
• Implement best practices for governance, compliance, and reproducibility
Key Skills & Expertise
• Strong programming skills in Python
• Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
• Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, SageMaker, Azure ML
• Knowledge of CI/CD tools: Jenkins, GitHub Actions, GitLab CI
• Experience with cloud platforms: AWS
• Strong understanding of data pipelines, ETL processes, and distributed systems
One of our clients is currently hiring for the position of MLOps Engineer Please find the job details below. If you are interested, kindly share your most recent resume at []
Role : MLOps Engineer
Location : Scottsdale AZ (100% Onsite)
Hire Type : Contract / Full time
Role Overview
We are looking for a skilled MLOps Engineer to design, deploy, and manage scalable machine learning pipelines in production. The role focuses on enabling seamless integration of ML models into enterprise systems with reliability, automation, and governance.
Key Responsibilities
• Design and implement end-to-end ML pipelines from data ingestion to model deployment
• Build and manage CI/CD pipelines for ML models (training, testing, deployment)
• Automate model monitoring, retraining, and performance optimization
• Collaborate with Data Scientists and Data Engineers for productionizing ML models
• Ensure scalability, reliability, and security of ML systems
• Manage model versioning, experiment tracking, and lifecycle management
• Implement best practices for governance, compliance, and reproducibility
Key Skills & Expertise
• Strong programming skills in Python
• Experience with ML frameworks: TensorFlow, PyTorch, Scikit-learn
• Hands-on experience with MLOps tools: MLflow, Kubeflow, Airflow, SageMaker, Azure ML
• Knowledge of CI/CD tools: Jenkins, GitHub Actions, GitLab CI
• Experience with cloud platforms: AWS
• Strong understanding of data pipelines, ETL processes, and distributed systems






