Job Details

Paid internship in AI Transformation B2B team at Sber, focusing on LLM agent design. Location: Moscow. Duration: 3 months. Workload: 30-40 hours/week. Opportunity for Junior Data Scientist/AI Engineer roles.

The AI Transformation B2B team at Sber implements AI and ML in pricing processes for B2B banking products. This internship focuses on developing GenAI agents and agent systems based on LLMs, providing practical experience with real tasks. The goal is to immerse strong technical candidates in LLM-based agent system design over 3 months.

Strong technical candidates interested in GenAI, LLM, and agent systems. Ideal candidate: - Final year Master's student, recent Master's graduate, or PhD student. - Strong mathematical, technical, or engineering background. - Proficient in Python. - Ability to quickly learn new libraries, frameworks, and approaches. - Willingness to deeply understand solution architecture. Separate advantage: - Education from a strong technical faculty (e.g., MIPT, MSU MechMat, MSU VMK, MSU MechMath, PMI, Applied Mathematics/Informatics). Experience is a plus: - GenAI solutions development (LangChain, LangGraph). - RAG systems construction. - Vector databases (FAISS, Chroma, Qdrant). - Open-source LLMs (Llama, Mistral, Qwen). - Understanding of neural network architectures (MLP, CNN, RNN/LSTM, Transformers). - Classic ML, MLOps, DevOps, or backend development experience. - Industrial development experience (API, services, containerization, CI/CD). Also welcome: Strong engineers from development, ML, MLOps, or DevOps looking to transition into GenAI and AI Agents.

- Paid internship in a rapidly growing AI field. - Work on real business tasks. - Deep dive into LLM agent and agent system design. - Access to internal stack and tools. - Unlimited GigaCode developer agent tariff. - Opportunity to receive an offer for a Junior Data Scientist / Junior AI Engineer position upon completion.