AI ML Engineer

RESPONSIBILITIES: Kforce has a client in Lakeland, FL that is seeking an AI ML Engineer to spearhead the buildout of our internal, company-wide compliance AI ecosystem. This role operates in a strict, privacy-first, and highly regulated environment. The AI ML Engineer will be responsible for designing and deploying enterprise-grade AI solutions using open-source models engineered entirely on our internal, high-performance hardware clusters-ensuring absolute data isolation with zero reliance on e

ONLY W2, NO C2C Job Title AI/ML Engineer REMOTE 6 Month Contract to hire Must Haves Strong local (non-cloud) AI experience Deep experience with AI frameworks + pipelines RAG + vector database expertise Infrastructure + performance optimization (GPU / Kubernetes) Primary Skills * Local-First AI Expertise: Proven track record deploying and optimizing open-source LLMs (e.g., LLaMA, Mistral) in non-cloud, restricted, or air-gapped private infrastructures * Deep Framework Proficiency: Heavy hands-on

We are seeking a hands-on Senior AI Engineer who designs, builds, and operates production GenAI systems - agentic workflows, RAG pipelines, and LLM-backed services with real users and real SLAs. This is an engineering role, not a research role. The bar is reliability, latency, cost, observability, and safe deployment at scale, with end-to-end ownership from architecture through on-call. Typical workloads include enterprise knowledge platforms, conversational analytics, agentic automation, and LL

Experience: [48]years software engineering, including [2]+ building with LLMs Role summary The AI Engineer builds the application layer. This is the hands-on-keyboard role that turns an architecture into a working, integrated, production-grade AI system: RAG pipelines, agents, guardrails, and the integration that embeds them into client systems. The engineer must write code that runs unchanged in intent whether the model sits behind an Azure OpenAI endpoint, an AWS Bedrock endpoint, or a NIM mic