> Markdown version of [/jobs/ext/3628152-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/3628152-ai-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - **Company:** Job Cloud Inc. - **Location:** New Albany, IN, United States - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Python (Programming Language), Machine Learning, Tensorflow, Microsoft Copilot, Search Technologies, Software Deployment, Enterprise Software Applications, Pytorch, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Llamaindex, Generative AI, Agentic-AI, HuggingFace, Machine Learning Operations, Docker - **Published:** October 8, 2026 - **Apply:** https://www.disabledperson.com/jobs/75914880-ai-ml-engineer ## About the Role * Strong Python programming. * Experience with PyTorch, TensorFlow, and/or Hugging Face. * Hands-on experience with LLMs, RAG, embeddings, vector databases, and prompt engineering. * Experience with cloud platforms such as AWS, Azure, or GCP. * Experience with APIs, Docker, CI/CD, and production ML systems. * Strong communication, problem-solving, and stakeholder-management skills. Preferred Skills: * Agentic AI, tool calling, LangChain, LlamaIndex, or DSPy. * Fine-tuning, model evaluation, observability, and Responsible AI. * Experience with AI privacy and security practices. ## Description We are looking for an experienced AI/ML Engineer to build and deploy production-ready AI/ML solutions, including LLM applications, copilots, AI agents, automation, and RAG-based systems., * Design, develop, and deploy LLM and Generative AI applications. * Build RAG pipelines, embeddings, vector search, and AI agents. * Integrate AI/ML models with APIs and enterprise applications. * Develop model evaluations, fine-tuning, guardrails, and monitoring. * Build reliable ML pipelines and support MLOps, CI/CD, and production deployments. * Collaborate with engineering, product, and business teams.