ML Engineer

Job Title Pay Range: $55.00hr - $60.00hr Requirement/Must Have Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval systems. Design, develop, and deploy Custom AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models. Implement and manipulate complex algorithms essential for developing and optimizing generative AI models. Manage data pipelines involving data pre-processing, augmentation, and synthetic data generation to enhance model training and performance. Ensure robust data handling practices including cleaning, labeling, and structuring datasets for generative AI workflows. Design MS Copilot Studio Agent Builder advanced skills, including custom plugin development, adaptive orchestration of multiple AI skills and APIs, contextual memory management, dynamic prompt engineering, and secure data handling. Build multi-turn agents that adapt and chain AI skills and APIs. Configure message, data, scheduled, and webhook triggers. Design workflows with Power Automate for task automation. Create logical, scalable flows for complex business processes. Use Copilot's built-in connectors to integrate enterprise apps and services seamlessly. Responsibilities Demonstrate advanced programming expertise, particularly in Python, with deep proficiency in AI-centric libraries such as TensorFlow, PyTorch, and Hugging Face Transformers. Architect and implement Retrieval-Augmented Generation (RAG) pipelines to enhance model performance using external knowledge sources, including document chunking, embedding generation, and retrieval systems. Design, develop, and deploy Custom AI agents capable of autonomous decision-making and task execution using LLMs and multi-modal models. Implement and manipulate complex algorithms essential for developing and optimizing generative AI models. Manage data pipelines involving data pre-processing, augmentation, and synthetic data generation to enhance model training and performance. Ensure robust data handling practices including cleaning, labeling, and structuring datasets for generative AI workflows. Design MS Copilot Studio Agent Builder advanced skills, including custom plugin development, adaptive orchestration of multiple AI skills and APIs, contextual memory management, dynamic prompt engineering, and secure data handling. Agent Orchestration: Build multi-turn agents that adapt and chain AI skills and APIs. Trigger Management: Configure message, data, scheduled, and webhook triggers. Automation Workflow: Design workflows with Power Automate for task automation. Flow Design: Create logical, scalable flows for complex business processes. Tool Integration: Use Copilot's built-in connectors to integrate enterprise apps and services seamlessly. Nice to Have Prompt engineering and secure data handling. Skills ML. Python. TensorFlow. PyTorch. Hugging Face Transformers. LLMs. Multi-modal models. RAG pipelines. MS Copilot Studio Agent Builder. Power Automate. Cynet Systems