Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer on a 4-month remote contract (EST hours) with a pay rate of $75.00+ hourly. Key skills include Kubernetes, Azure cloud, and experience in ML Ops, Data Engineering, and DevOps.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
600
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πŸ—“οΈ - Date discovered
August 20, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
Remote
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
United States
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🧠 - Skills detailed
#Azure cloud #Azure DevOps #ML Ops (Machine Learning Operations) #Data Science #Data Engineering #Docker #Azure #ML (Machine Learning) #Kubernetes #Databricks #Scala #Cloud #AI (Artificial Intelligence) #DevOps
Role description
Machine Learning Engineer Location: remote (EST hours) Duration: 4-month contract Pay: $75.00+ hourly Job Description We are looking for an experienced Machine Learning Operations Engineer who has experience working with design, development and implementation of AI/ML applications and managing the lifecycle of Machine Learning models. The role of an MLOps Engineer is at intersection of Data Scientist, Data Engineer, and DevOps Engineer. You'll be working in a team of engineers that takes on a wide array of responsibilities that encompass building all the infrastructure necessary to take a trained ML Model , integrate and deploy, making it available to other applications. Responsibilities β€’ Design and deploy scalable infrastructure for ML workloads using cloud platforms and containerization technologies (e.g., Docker, Kubernetes) β€’ Work with teams to design and build cloud hosted, automated pipelines that run, monitor, and retrain ML Models for business applications β€’ Design and implement Model and Pipeline validation procedures alongside teams of Data Scientists, Data Engineers, and other ML Engineers β€’ Optimize and refactor development code so that it can be moved to production β€’ Build Data, Feature Engineering Pipelines for new and existing models β€’ Assemble configurations and specifications to automatically build environments in production β€’ Create and develop in CI/CD Pipelines which allow for controlled and continuous enhancement of existing work and new features during both development and production phases REQUIREMENTS β€’ Experience with Kubernetes, AKS, Azure cloud, Azure DevOps, Databricks Category Code: JN008