MLOps Lead
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an MLOps Lead in Dallas, TX, offering a hybrid contract of 2-3 days onsite weekly. Requires 10+ years of experience, 4+ in MLOps, AWS proficiency, Python coding, and knowledge of ML frameworks like TensorFlow or PyTorch.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 3, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Hybrid
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#Terraform #Documentation #Automation #PyTorch #Infrastructure as Code (IaC) #ML (Machine Learning) #AWS (Amazon Web Services) #Lambda (AWS Lambda) #SageMaker #DevOps #Docker #GitHub #Monitoring #TensorFlow #Python #S3 (Amazon Simple Storage Service)
Role description
Title- MLOps Lead
Location- Dallas TX (Locals Preferred) for onsite work, 2-3 days/ week
Required Skills:
• Overall 10+ years of experience with 4+ years of experience in MLOps, Machine Learning Engineering, or a related DevOps role with a focus on ML workflows
• Extensive hands-on experience in designing and implementing MLOps solutions on AWS. Proficient with core services like SageMaker, S3, ECS, EKS, Lambda
• Strong coding proficiency in Python. Extensive experience with automation tools, including Terraform for IaC and GitHub Actions.
• A solid understanding of MLOps and DevOps principles. Hands-on experience with MLOps frameworks like Sagemaker Pipelines, Model Registry, Weights.
• Expertise in developing and deploying containerized applications using Docker and orchestrating them with ECS and EKS.
• Experience with model testing, validation, and performance monitoring.
• Good understanding of ML frameworks like PyTorch or TensorFlow is required .
• Excellent communication and documentation skills, with a proven ability to collaborate with cross-functional teams.
Title- MLOps Lead
Location- Dallas TX (Locals Preferred) for onsite work, 2-3 days/ week
Required Skills:
• Overall 10+ years of experience with 4+ years of experience in MLOps, Machine Learning Engineering, or a related DevOps role with a focus on ML workflows
• Extensive hands-on experience in designing and implementing MLOps solutions on AWS. Proficient with core services like SageMaker, S3, ECS, EKS, Lambda
• Strong coding proficiency in Python. Extensive experience with automation tools, including Terraform for IaC and GitHub Actions.
• A solid understanding of MLOps and DevOps principles. Hands-on experience with MLOps frameworks like Sagemaker Pipelines, Model Registry, Weights.
• Expertise in developing and deploying containerized applications using Docker and orchestrating them with ECS and EKS.
• Experience with model testing, validation, and performance monitoring.
• Good understanding of ML frameworks like PyTorch or TensorFlow is required .
• Excellent communication and documentation skills, with a proven ability to collaborate with cross-functional teams.
