Taras Technology LLC
Sr AI/ML Cloud Engineer - 100% Remote
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr AI/ML Cloud Engineer with 8-15 years of experience, offering a 100% remote contract. Key skills include AWS, Azure, Google Cloud, Python, TensorFlow, and MLOps. Familiarity with Google Cloud and AI compliance is preferred.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
November 5, 2025
🕒 - Duration
Unknown
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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
#Data Lake #ML (Machine Learning) #AI (Artificial Intelligence) #Data Encryption #IAM (Identity and Access Management) #"ETL (Extract #Transform #Load)" #BigQuery #AutoScaling #Python #Storage #TensorFlow #SageMaker #Cloud #Synapse #Security #Deployment #PyTorch #S3 (Amazon Simple Storage Service) #Monitoring #AWS (Amazon Web Services) #MLflow #Compliance #Azure #Data Engineering #Model Deployment #AWS SageMaker #Data Processing
Role description
Role 1: AI/ML Cloud Engineer (3 Positions)
Experience range: 8-15 years
Location: US (Remote)
Job Description:
• Cloud Infrastructure: Build and manage compute, storage, and networking for AI/ML workloads using platforms like AWS, Azure, or Google Cloud.
• MLOps/AIOps: Automate model deployment, monitoring, and retraining using tools like Kube Flow, MLflow, or SageMaker Pipelines. AWS (SageMaker, ECS, S3), Google Cloud (Vertex AI, BigQuery), Azure (AI Studio, Synapse) Python, TensorFlow, PyTorch, scikit-learn, Cursor Coding
• Data Engineering: Set up data lakes, ETL pipelines, and real-time data processing systems for AI models.
• Cost & Performance Optimization: Optimize GPU/TPU usage, autoscaling, and cloud resource management for high-efficiency AI systems.
• Security & Compliance: Implement IAM, data encryption, and compliance policies for AI data and models.
• Good to have primary Google cloud specific skill sets (including Enterprise Gemini AI experience)
“Taras Technology, LLC is an EEO/AA Employer: women, minorities, the disabled and veterans are encouraged to apply”
Role 1: AI/ML Cloud Engineer (3 Positions)
Experience range: 8-15 years
Location: US (Remote)
Job Description:
• Cloud Infrastructure: Build and manage compute, storage, and networking for AI/ML workloads using platforms like AWS, Azure, or Google Cloud.
• MLOps/AIOps: Automate model deployment, monitoring, and retraining using tools like Kube Flow, MLflow, or SageMaker Pipelines. AWS (SageMaker, ECS, S3), Google Cloud (Vertex AI, BigQuery), Azure (AI Studio, Synapse) Python, TensorFlow, PyTorch, scikit-learn, Cursor Coding
• Data Engineering: Set up data lakes, ETL pipelines, and real-time data processing systems for AI models.
• Cost & Performance Optimization: Optimize GPU/TPU usage, autoscaling, and cloud resource management for high-efficiency AI systems.
• Security & Compliance: Implement IAM, data encryption, and compliance policies for AI data and models.
• Good to have primary Google cloud specific skill sets (including Enterprise Gemini AI experience)
“Taras Technology, LLC is an EEO/AA Employer: women, minorities, the disabled and veterans are encouraged to apply”
