Tekskills Inc.

AI/ML Ops Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Ops Engineer, offering a 12+ month remote contract with a pay rate of "unknown." Key skills include hands-on experience with Generative and Agentic AI platforms, MCP server management, and familiarity with cloud platforms (Azure, AWS, GCP).
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 19, 2025
🕒 - Duration
More than 6 months
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Cloud #Data Science #Docker #ML (Machine Learning) #Kubernetes #AI (Artificial Intelligence) #ML Ops (Machine Learning Operations) #Security #Deployment #Compliance #Azure #GCP (Google Cloud Platform) #AWS (Amazon Web Services)
Role description
Job Title: AI/ML Ops Engineer Location: Remote Duration: 12+ months Job Details: We are seeking an experienced AI/ML Ops Engineer to provide operational support for cutting-edge AI platforms, including Generative AI and Agentic AI systems. The ideal candidate will have hands-on experience in managing AI infrastructure and resolving technical issues related to AI platforms. Key Responsibilities: • Provide first-line support for Generative AI and Agentic AI-related queries and issues. • Troubleshoot and resolve tickets related to Gen AI and Agentic AI platforms. • Manage and maintain MCP servers and related infrastructure. • Collaborate with development and data science teams to ensure smooth deployment and operation of AI models. • Monitor system performance and implement best practices for AI/ML operational efficiency. Required Skills & Experience: • Hands-on experience with Generative AI and Agentic AI platforms. • Strong understanding of MCP servers and AI infrastructure. • Proven ability to resolve technical issues and support AI/ML systems. • Familiarity with AI/ML lifecycle management and operational workflows. • Excellent problem-solving and communication skills. Preferred Qualifications: • Experience with cloud platforms (Azure, AWS, GCP) for AI/ML deployments. • Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines. • Understanding of AI security and compliance best practices.