We are seeking a highly skilled AI/ML Engineer to design, develop, and deploy cutting-edge artificial intelligence and machine learning solutions, with a strong focus on Retrieval-Augmented Generation (RAG) systems. The ideal candidate will have hands-on experience building scalable pipelines for unstructured data, optimizing semantic retrieval, and working with modern large language models (LLMs). This role requires collaboration with cross-functional teams to deliver high-impact, production-ready AI solutions. Key Responsibilities: Design, develop, and deploy advanced AI/ML and RAG-based solutions. Build and maintain custom RAG systems leveraging internal data sources. Develop robust data pipelines for processing and managing unstructured content. Optimize semantic search and retrieval performance using embeddings and vector databases. Evaluate model performance using key quality metrics and continuously improve system accuracy. Collaborate with cross-functional teams to design and deploy agentic RAG solutions. Work with leading large language models (LLMs) and conduct experiments to enhance performance. Stay up to date with the latest advancements in AI/ML, NLP, and generative AI technologies. Develop and maintain RESTful APIs for AI services. Required Technical Skills: Programming: Strong proficiency in Python, including libraries such as NumPy and Pandas; solid SQL skills. Frameworks & Libraries: FastAPI, Uvicorn (ASGI Server), Pydantic, Pydantic-Settings, LangChain, Hugging Face Transformers. Machine Learning/NLP: Deep Learning, Natural Language Processing (NLP), text embeddings, semantic search, and model evaluation techniques. Vector Databases: Experience with pgVector. Testing: Experience with pytest (v8.4.1 or similar). Deployment & DevOps: Docker, OpenShift, Jenkins (CI/CD pipelines). Tools & Practices: Git, RESTful API development, and version control best practices. Preferred Qualifications: Experience working with agentic AI systems or autonomous workflows. Familiarity with scalable architecture for AI systems in production. Strong problem-solving skills and ability to work in a collaborative environment. Soft Skills: Strong communication and teamwork skills. Ability to manage multiple priorities in a fast-paced environment.
