Careers
Senior AI/ML Software Engineer
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.
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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.
- Agile development experience (Kanban, Scrum).
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
- Flexible working hours
- 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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