Machine Learning Engineer (Generative AI)

Machine Learning Engineer (Generative AI) Location: Charlotte, NC (Hybrid) Duration: 12 Month Contract Employment Type: W2 Only Overview We are seeking a highly skilled Machine Learning Engineer specializing in Generative AI to design, develop, and deploy cutting‑edge AI solutions that drive innovation across the enterprise. This role will focus on building scalable AI applications utilizing Large Language Models (LLMs), retrieval‑augmented generation (RAG), agentic AI frameworks, and modern machine learning technologies. The ideal candidate combines strong software engineering fundamentals with hands‑on experience developing and deploying production‑grade AI solutions. This individual will partner closely with engineering teams, architects, and business stakeholders to build intelligent systems that solve complex business challenges and support enterprise‑scale initiatives. Key Responsibilities Design, develop, test, and deploy Generative AI solutions for text, image, and multimodal applications. Build and optimize Large Language Model (LLM) applications using modern AI frameworks and tooling. Develop advanced prompt engineering strategies and context‑aware AI workflows. Design and implement Retrieval‑Augmented Generation (RAG) architectures utilizing vector databases and semantic search techniques. Build agentic AI applications leveraging multi‑agent frameworks, memory management, session handling, and Model Context Protocol (MCP) tools. Integrate AI capabilities into enterprise applications, APIs, and business workflows. Collaborate with cross‑functional teams to define technical requirements and AI solution architecture. Lead complex technology initiatives with enterprise‑wide impact and influence AI engineering best practices. Evaluate emerging AI technologies and recommend innovative solutions to improve business outcomes. Develop scalable, secure, and maintainable AI applications following software engineering best practices. Participate in code reviews, architecture discussions, testing, debugging, and technical documentation. Mentor engineers and contribute to the development of AI engineering standards and best practices. Support MLOps initiatives to ensure reliable deployment, monitoring, and lifecycle management of AI models. Required Qualifications 5+ years of Software Engineering or Machine Learning Engineering experience, or equivalent combination of education, military experience, training, and professional experience. Strong proficiency in Python development. Experience with machine learning frameworks such as PyTorch and TensorFlow. Hands‑on experience building solutions with Large Language Models (LLMs), transformer architectures, and the Hugging Face ecosystem. Experience developing multi‑agent AI systems utilizing session management, memory frameworks, and MCP tools. Knowledge of vector databases and Retrieval‑Augmented Generation (RAG) architectures. Experience building and deploying scalable AI applications in enterprise environments. Strong understanding of software engineering principles, design patterns, and distributed systems. Excellent problem‑solving, communication, and collaboration skills. Preferred Qualifications Experience with cloud‑based AI platforms including: AWS SageMaker Azure OpenAI Google Vertex AI Experience implementing MLOps practices, model deployment pipelines, and AI lifecycle management. Experience integrating AI solutions into web applications and enterprise platforms. Familiarity with containerization technologies and cloud‑native architectures. Experience building multimodal AI applications. Understanding of AI governance, security, and responsible AI practices. Desired Technical Skills Python PyTorch TensorFlow Hugging Face Large Language Models (LLMs) Prompt Engineering Retrieval‑Augmented Generation (RAG) Vector Databases Semantic Search Multi‑Agent Systems MCP (Model Context Protocol) AWS SageMaker Azure OpenAI Google Vertex AI MLOps REST APIs Cloud‑Native Application Development #J-18808-Ljbffr Strategic Staffing Solutions