Are you passionate about building AI systems that make a real impact? Do you enjoy turning research into production-ready solutions?
We are looking for an AI & ML Engineer to join a team creating advanced AI/ML applications across fraud prevention, risk management, and operational optimization. You will work on end-to-end ML workflows , including generative and agentic AI solutions, and help scale LLM deployments on GPU clusters using modern MLOps and AIOps practices.
What you’ll do:

• Design, develop, and deploy AI/ML applications, including RAG systems and agentic AI workflows
• Optimize LLM training and inference across GPU clusters using Kubernetes and AIOps tools ⚡
• Turn prototypes into production-ready systems
• Explore and experiment with cutting-edge AI/ML methods and technologies
• Contribute to improving internal practices and workflows for AI operations
• Maintain and support AI-related infrastructure and tools

What we’re looking for:
Must-haves:

• 4+ years of experience building and maintaining ML systems (PhD counts)
• Strong Python skills
• Solid Linux experience ️
• Experience with complex computational or scientific modeling
• Understanding of MLOps, AIOps, and deploying AI systems in production

Nice-to-haves:

• Hands-on experience with LLMs, RAG systems, or agentic AI
• Familiarity with Kubernetes ecosystem (Helm, ArgoCD)
• Projects or experience with open-source LLM tools (vLLM, llama.cpp, open-webui)
• Knowledge of parallel or distributed computing
• Experience with UI frameworks like Streamlit or Svelte for AI prototypes
• Basic SQL or workflow orchestration (Airflow)