October 09, 2026 • Moscow • PJSC Sberbank • IT: Data Science and Data Engineering
No experience required
Our team is developing the next generation of intelligent systems for risk analysis. Our projects include:
- development of NLP models based on LLMs, creation of SOTA AI agents and multi-agent systems for operational and ESG risks;
- creation of transformer-based models for solving banking problems on financial data; financial market modeling using machine learning;
- development of classic ML models for the lending process, which are the core of Sber's business and a key profit driver.
And now our team is looking for talented interns in three areas: Data Scientist, LLM Researcher, and Quant-Risks in the Risk Modeling Department.
Responsibilities
- development of PoC and MVP AI agents based on LLMs using LLM frameworks such as langchain/langgraph
- adaptation and training of Sber's LLMs using internal and external data (Prompt Tuning, LoRA, SFT, GRPO)
- application of RL approaches to improve the model's reasoning abilities.
Requirements
- student status (bachelor's/master's) at the time of employment
- knowledge of statistics and ML/DL algorithms
- knowledge of Python and the ML stack (PyTorch, Scikit-learn, Pandas)
- understanding of modern NLP (tokenization, data processing, embeddings, pre-train models, etc.)
- experience in designing and training neural network models (from CNN/RNN to transformers)
- experience in building RAG (classic RAG, GraphRAG, Agentic RAG)
- knowledge of classic algorithms (two pointers, binary search) and data structures (heap, stack, binary tree)
- confident English for reading and analyzing scientific articles and documentation
Conditions
- work format: office in Moscow, near Kutuzovsky Prospekt metro station
- flexible schedule and the ability to combine with studies: 30 to 40 hours per week
- opportunity to engage in sports at one of the bank's gyms
- free SberPrime+ subscription, discounts on products from partner companies
- reward for recommending friends to the Sber team.
