We are hiring an AI/ML Engineer for a project focused on developing an advanced Large Language Model (LLM)-based intelligent agent. The project integrates cutting-edge AI/ML frameworks to enhance interpretability and decision-making in artificial intelligence. Our research-driven approach leverages mathematical methods, such as abstract algebra, to push the boundaries of AI cognitive capabilities. The ultimate goal is to create a system capable of logical reasoning and complex problem-solving. Requirements Strong Python programming skills with experience in AI/ML frameworks (PyTorch, TensorFlow, etc.). Hands-on experience with agent-based AI frameworks (LangChain, LangGraph, CrewAI). Understanding of LLMs (GPT models) and their practical applications. Mathematical background (familiarity with abstract algebra or advanced math concepts is a plus). Cloud deployment experience (AWS, Azure, GCP) and knowledge of Docker/Kubernetes. Excellent collaboration and communication skills, with experience working in research-driven AI projects. Would be a plus Master’s or Ph.D. in Computer Science, Mathematics, Data Science, or a related field. Proven experience in research-oriented AI/ML projects or developing intelligent agents. We offer Growing company with great opportunities for development. Full remote work. Competitive market salary, annual paid vacation, paid sick leaves, and holidays. Friendly and experienced team. Responsibilities Develop an LLM-based intelligent agent using Python and modern AI frameworks (LangChain, LangGraph, CrewAI). Implement mathematical techniques (e.g., abstract algebra) to enhance AI reasoning and decision-making. Design and build tools that improve AI/ML interpretability and cognitive simulation. Collaborate with researchers to integrate mathematical frameworks into AI models. Manage and maintain a structured codebase in Git (GitHub), ensuring high-quality coding standards. Deploy the system on cloud infrastructure (AWS, Azure, or GCP) with automation and scalability in mind. Document system architecture and workflows, ensuring clarity for future development. Participate in an agile workflow using Kanban methodology, with weekly progress reviews and stakeholder engagement.

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