Quantum World Technologies Inc.
Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist with a contract length of "unknown," offering a pay rate of "unknown." Key skills include Azure, Python, GCP, and AI. Experience in model deployment and data pipeline automation is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
December 12, 2025
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
-
🔒 - Security
Unknown
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📍 - Location detailed
United States
-
🧠 - Skills detailed
#ML (Machine Learning) #Automation #Model Deployment #Azure #CMS (Content Management System) #Data Ingestion #Data Science #DevOps #GCP (Google Cloud Platform) #AI (Artificial Intelligence) #Deployment #Python #Data Pipeline #Cloud #Data Engineering
Role description
Key Responsibilities:
• Participate in developing Generative AI & Traditional AI Platform Capabilities on enterprise on-prem and cloud platforms.
• Primary responsibilities include working on vector database, creating index, writing python code for data ingestion, working with content management systems to parse, chunk data
• Primary responsibilities also include Vector Database Build on GCP and Azure and building associated data pipeline for Vector Database, Document AI
• Responsible for AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI, Azure ML)
• Building automation capabilities to deploy ML Models and LLM Models on the enterprise on-prem platform and cloud platform.
• Build and Deploy capabilities for automating model scoring/Inferencing of ML models and LLMs.
• Build and Deploy capabilities for data pipeline deployment standardization and model consumption by multiple LOBs.
• Collaborate with product owners, devOps team, data scientists, support teams to define and drive end to end model scoring pipelines.
• Participate in day-to-day standups for platform capability build.
• Provide SME guidance for data science teams on software engineering principles, model deployments, platform capabilities.
• Drive AI use case delivery end to end collaborating with Data scientists, Data Engineers, LOB Technology using standardized platform processes and capabilities.
• Support Production Issues partnering with production support.
Key Responsibilities:
• Participate in developing Generative AI & Traditional AI Platform Capabilities on enterprise on-prem and cloud platforms.
• Primary responsibilities include working on vector database, creating index, writing python code for data ingestion, working with content management systems to parse, chunk data
• Primary responsibilities also include Vector Database Build on GCP and Azure and building associated data pipeline for Vector Database, Document AI
• Responsible for AI model delivery to on-prem infrastructure and cloud platforms (GCP-Vertex AI, Azure ML)
• Building automation capabilities to deploy ML Models and LLM Models on the enterprise on-prem platform and cloud platform.
• Build and Deploy capabilities for automating model scoring/Inferencing of ML models and LLMs.
• Build and Deploy capabilities for data pipeline deployment standardization and model consumption by multiple LOBs.
• Collaborate with product owners, devOps team, data scientists, support teams to define and drive end to end model scoring pipelines.
• Participate in day-to-day standups for platform capability build.
• Provide SME guidance for data science teams on software engineering principles, model deployments, platform capabilities.
• Drive AI use case delivery end to end collaborating with Data scientists, Data Engineers, LOB Technology using standardized platform processes and capabilities.
• Support Production Issues partnering with production support.
