Infoshare Systems, Inc.
Data Science AI ML Analytics
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a contract position for Data Science AI ML Analytics in Pittsburgh, PA, requiring expertise in Python, PyTorch, TensorFlow, and LangChain. Key responsibilities include developing ML/DL models and deploying LLM-powered solutions using MLOps practices.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 2, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Pittsburgh, PA
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🧠 - Skills detailed
#ML (Machine Learning) #Python #AI (Artificial Intelligence) #Databases #Data Science #Model Evaluation #Langchain #PyTorch #TensorFlow #Cloud #Data Analysis
Role description
Job Title: Data Science Analytics | AI ML
Location: Pittsburgh, PA
Duration: Contract
Responsibilities: Design and develop ML/DL models using Python, PyTorch, and TensorFlow for analytics and AI applications Build and deploy LLM-powered solutions including RAG pipelines, agents, and chatbots using LangChain/Llama Index Perform data analysis, feature engineering, and model evaluation on large structured/unstructured data sets Fine-tune and optimize LLMs, implement vector databases, and improve retrieval accuracy Collaborate with engineering, product, and business teams to translate requirements into AI solutions Deploy models to production using MLOps best practices on cloud platforms
Job Title: Data Science Analytics | AI ML
Location: Pittsburgh, PA
Duration: Contract
Responsibilities: Design and develop ML/DL models using Python, PyTorch, and TensorFlow for analytics and AI applications Build and deploy LLM-powered solutions including RAG pipelines, agents, and chatbots using LangChain/Llama Index Perform data analysis, feature engineering, and model evaluation on large structured/unstructured data sets Fine-tune and optimize LLMs, implement vector databases, and improve retrieval accuracy Collaborate with engineering, product, and business teams to translate requirements into AI solutions Deploy models to production using MLOps best practices on cloud platforms
