Machine Learning Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer with experience in software development and ML engineering. Contract length is unspecified, with a pay rate of "unknown." Key skills include Python, cloud environments (AWS, GCP), model deployment, and familiarity with CI/CD processes.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
-
🗓️ - Date discovered
May 25, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Irving, TX
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🧠 - Skills detailed
#Deployment #Python #AWS (Amazon Web Services) #Airflow #DevOps #Jenkins #Cloud #Data Engineering #ML (Machine Learning) #Model Deployment #Programming #Data Science #GCP (Google Cloud Platform)
Role description
• Experience in software development/ML Engineering jobs.
• Model deployment, configuration, unit test, wrapper development, feature engineering, etc.
• Experience with Python programming
• Experience in cloud based development and production environments - AWS, GCP and On-prem clusters
• Familiarity with large scale cloud-based platform/pipeline development and productization.
• Have experience with basic ML practices and standard workflows.
Even better if you have one or more of the following:
• Understand data science concepts and common needs from data scientists and data engineers.
• Strong collaboration skills and communication skills, especially when involving (non-tech) business stakeholders.
• Familiar with CI/CD processes and common frameworks, like Jenkins, Airflow, etc.
• Familiar with MLOps/DevOps.
• Experience in software development/ML Engineering jobs.
• Model deployment, configuration, unit test, wrapper development, feature engineering, etc.
• Experience with Python programming
• Experience in cloud based development and production environments - AWS, GCP and On-prem clusters
• Familiarity with large scale cloud-based platform/pipeline development and productization.
• Have experience with basic ML practices and standard workflows.
Even better if you have one or more of the following:
• Understand data science concepts and common needs from data scientists and data engineers.
• Strong collaboration skills and communication skills, especially when involving (non-tech) business stakeholders.
• Familiar with CI/CD processes and common frameworks, like Jenkins, Airflow, etc.
• Familiar with MLOps/DevOps.
