AI/ML Engineering Senior Advisor - Msut Live in IL - No H1B
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This role is for an AI/ML Engineering Senior Advisor, C2H, long-term, located in Illinois. Requires 7+ years in machine learning, strong Python skills, experience with TensorFlow, PyTorch, and cloud deployment (Azure preferred). LLM/GenAI experience is essential.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
May 30, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Illinois, United States
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🧠 - Skills detailed
#OpenCV (Open Source Computer Vision Library) #AWS (Amazon Web Services) #GIT #REST (Representational State Transfer) #ML (Machine Learning) #Cloud #Langchain #Python #REST API #GCP (Google Cloud Platform) #Deployment #Deep Learning #AI (Artificial Intelligence) #Automation #PyTorch #Azure #Transformers #Statistics #"ETL (Extract #Transform #Load)" #Object Detection #Keras #Kubernetes #FastAPI #MLflow #Docker #TensorFlow
Role description
Employment Type: C2H
Duration: Long Term
Key Technology: Python, TensorFlow, PyTorch, Keras, OpenCV, DVC, MLflow, Git, CI/CD
Job Responsibilities:
• Work on ML Solution for RxQuality for MFC Project
Required:
• 7+ years of hands-on experience in applied machine learning, deep learning, and AI system deployment
• Strong Python engineering background with ML/DL frameworks: TensorFlow, PyTorch, Keras, OpenCV
• Proven experience in Computer Vision tasks, including object detection, segmentation, and OCR
• Experience training and fine-tuning models such as: YOLOv5/v8, EfficientNet, Faster-RCNN, TrOCR, Vision Transformers (ViT)
• Practical experience building and serving REST APIs for inference (TF Serving, TorchServe, FastAPI)
• Hands-on with MLOps tools: DVC, MLflow, Git, CI/CD, containerization (Docker/Kubernetes)
• Cloud deployment experience (Azure preferred; AWS or GCP acceptable)
• LLM/GenAI experience: building, fine-tuning, or prompting models such as GPT-4, LLaMA, Claude, etc.
• Familiarity with RAG (Retrieval-Augmented Generation) pipelines and integration into enterprise systems
• Understanding of Agentic AI architectures (e.g., LangChain, CrewAI, AutoGPT) for orchestrated task agents or workflow automation
• Strong foundations in statistics, optimization, and deep learning principles
• Clear understanding of AI governance, fairness, and model explainability
Employment Type: C2H
Duration: Long Term
Key Technology: Python, TensorFlow, PyTorch, Keras, OpenCV, DVC, MLflow, Git, CI/CD
Job Responsibilities:
• Work on ML Solution for RxQuality for MFC Project
Required:
• 7+ years of hands-on experience in applied machine learning, deep learning, and AI system deployment
• Strong Python engineering background with ML/DL frameworks: TensorFlow, PyTorch, Keras, OpenCV
• Proven experience in Computer Vision tasks, including object detection, segmentation, and OCR
• Experience training and fine-tuning models such as: YOLOv5/v8, EfficientNet, Faster-RCNN, TrOCR, Vision Transformers (ViT)
• Practical experience building and serving REST APIs for inference (TF Serving, TorchServe, FastAPI)
• Hands-on with MLOps tools: DVC, MLflow, Git, CI/CD, containerization (Docker/Kubernetes)
• Cloud deployment experience (Azure preferred; AWS or GCP acceptable)
• LLM/GenAI experience: building, fine-tuning, or prompting models such as GPT-4, LLaMA, Claude, etc.
• Familiarity with RAG (Retrieval-Augmented Generation) pipelines and integration into enterprise systems
• Understanding of Agentic AI architectures (e.g., LangChain, CrewAI, AutoGPT) for orchestrated task agents or workflow automation
• Strong foundations in statistics, optimization, and deep learning principles
• Clear understanding of AI governance, fairness, and model explainability
