Highbrow
Overview
Job Title:
AI/ML Engineering Senior Advisor Job ID: 2025-13489 Job Location: Deerfield, IL (Hybrid 3 days/week onsite) # Positions: 1 Work Eligibility: All Work Authorizations are Permitted No Visa Transfers What You Will Do
Work on ML Solution for RxQuality for MFC Project Responsibilities
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
#J-18808-Ljbffr
Job Title:
AI/ML Engineering Senior Advisor Job ID: 2025-13489 Job Location: Deerfield, IL (Hybrid 3 days/week onsite) # Positions: 1 Work Eligibility: All Work Authorizations are Permitted No Visa Transfers What You Will Do
Work on ML Solution for RxQuality for MFC Project Responsibilities
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
#J-18808-Ljbffr