

DevOps Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a DevOps Engineer specializing in Gen AI, located in Princeton, NJ. Contract length and pay rate are unspecified. Key skills include Azure Machine Learning, Python, Docker, and Kubernetes, with experience in MLOps and DevSecOps practices required.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
July 10, 2025
π - Project duration
Unknown
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ποΈ - Location type
On-site
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
Princeton, NJ
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π§ - Skills detailed
#Kubernetes #Compliance #Model Deployment #Deployment #Scala #Grafana #DevSecOps #Prometheus #Docker #Monitoring #ML (Machine Learning) #DevOps #AI (Artificial Intelligence) #Azure #Data Science #Azure DevOps #Python #Terraform #MLflow #Security #Azure Machine Learning
Role description
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Job Title : Devops Engineer with Gen AI
Location: Princeton, NJ
Primary Skills: GEN AI
β’ Document architecture, workflows, and best practices for knowledge sharing and compliance.
β’ Provide technical oversight & Guidelines
β’ Architect and implement end-to-end MLOps and LLMOps pipelines using Azure Machine Learning and Azure OpenAI.
β’ Design scalable infrastructure for training, deploying, and monitoring ML and LLM models in production.
β’ Collaborate with data scientists and engineers to streamline model development, testing, and deployment workflows.
β’ Manage Azure Kubernetes Service (AKS) clusters and containerized ML workloads.
β’ Ensure model governance, versioning, and reproducibility using tools like MLflow and Azure DevOps.
β’ Promote DevSecOps practices, ensuring security and compliance are embedded in the ML lifecycle.
β’ Monitor and troubleshoot production ML systems, ensuring high availability and performance.
β’ Experience with Azure Machine Learning, Azure OpenAI, Azure DevOps, and AKS.
β’ Proficiency in Python, Docker, Kubernetes, and CI/CD pipelines.
β’ Experience with LLM fine-tuning, prompt engineering, and model deployment.
β’ Familiarity with MLflow, Terraform, and monitoring tools like Prometheus/Grafana.