Sibitalent Corp
MLOPS Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOPS Engineer with a contract length of "unknown", offering a pay rate of "unknown". Key skills required include Python, ML frameworks (TensorFlow, PyTorch), MLOps tools (MLflow, Kubeflow), and cloud experience (AWS).
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 25, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Scottsdale, AZ
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🧠 - Skills detailed
#Data Pipeline #Airflow #Deployment #ML (Machine Learning) #Compliance #Programming #PyTorch #Azure #Model Deployment #SageMaker #MLflow #Data Engineering #Monitoring #Data Science #Python #TensorFlow #Security #Data Ingestion #Scala #Cloud #AWS (Amazon Web Services) #"ETL (Extract #Transform #Load)"
Role description
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: c
• Experience with cloud platforms: AWS
• Strong understanding of data pipelines, ETL processes, and distributed systems
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: c
• Experience with cloud platforms: AWS
• Strong understanding of data pipelines, ETL processes, and distributed systems
