Machine Learning Ops Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Ops Engineer with long-term contract potential, located in Westlake, TX (hybrid). Requires MLOps experience, proficiency in Python REST API development, AWS, CI/CD pipelines, Docker, and familiarity with Snowflake in a financial setting.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
September 25, 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
#Kubernetes #ML (Machine Learning) #AWS (Amazon Web Services) #Cloud #Data Science #Scala #Docker #Deployment #Jenkins #Snowflake #SageMaker #ML Ops (Machine Learning Operations) #REST API #REST (Representational State Transfer) #Python #API (Application Programming Interface) #Model Deployment
Role description
Please find the position details below:
Job Title: Machine Learning Ops Engineer
Location: Westlake, TX (Hybrid – 2 weeks onsite , 2 weeks remote)
Duration: Long term contract with possibility of Conversion
Interview: 2 rounds
What is the Client Looking For?
Role: Machine Learning Ops Engineer (MLOps Engineer)
Must-Have Skills:
• Experience with MLOps, especially using Sagemaker.
• Proficient in Python REST API development.
• Experience with AWS Cloud services.
• CI/CD pipeline experience, preferably Jenkins or similar tools.
• Containerization experience (Docker, Kubernetes).
• Experience in a large financial company.
• Familiarity with Snowflake data platform.
What is the Project?
The project is focused on developing and maintaining the Machine Learning Operations (MLOps) platform that supports Data Scientists. The team does not develop ML models but builds and administers the platform that enables ML model deployment, scalability, and integration.
Key responsibilities include:
• Developing and maintaining REST APIs in Python.
• Deploying and scaling ML models into production.
• Building CI/CD pipelines using Jenkins or similar tools.
• Automating infrastructure and workflows.
• Managing tools like Aerospike and container systems like Docker.
Please find the position details below:
Job Title: Machine Learning Ops Engineer
Location: Westlake, TX (Hybrid – 2 weeks onsite , 2 weeks remote)
Duration: Long term contract with possibility of Conversion
Interview: 2 rounds
What is the Client Looking For?
Role: Machine Learning Ops Engineer (MLOps Engineer)
Must-Have Skills:
• Experience with MLOps, especially using Sagemaker.
• Proficient in Python REST API development.
• Experience with AWS Cloud services.
• CI/CD pipeline experience, preferably Jenkins or similar tools.
• Containerization experience (Docker, Kubernetes).
• Experience in a large financial company.
• Familiarity with Snowflake data platform.
What is the Project?
The project is focused on developing and maintaining the Machine Learning Operations (MLOps) platform that supports Data Scientists. The team does not develop ML models but builds and administers the platform that enables ML model deployment, scalability, and integration.
Key responsibilities include:
• Developing and maintaining REST APIs in Python.
• Deploying and scaling ML models into production.
• Building CI/CD pipelines using Jenkins or similar tools.
• Automating infrastructure and workflows.
• Managing tools like Aerospike and container systems like Docker.
