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3-6 years
Experience
Full-time
Employment
Onsite
Work Format
Middle
Grade
Data Science & ML
Specialization
FinTech
Industry
Corporation
Company Type
Team Description:
Our team develops comprehensive AI solutions (Classic NLP, LLMs, AI agents) for the key products and processes of the 'Strategy and Development' Business Unit. We are always at the forefront of technological development and try new things – we were the first at Sber to develop a prototype of a multi-agent system for handling requests, which made agent-based solutions one of the most sought-after directions in the bank.
Our technological focus extends beyond AI agents: we solve tasks in classification, clustering, matching, domain adaptation (Metric Learning, PEFT), using SFT when necessary. The outcome of our work is not a separate e2e pipeline, but production-ready multi-service architectures integrated into Sber's internal surfaces.
Recent projects: a multi-agent system for analyzing organizational effectiveness (presentation at AI Journey 2025), a multi-agent pipeline for analyzing documents on organizational changes, an AI agent-Copilot for setting and monitoring goals. All areas are actively growing and receiving direct support from the bank's management.
Key Areas of Activity:
• We form recommendations for improving the efficiency of teams, products, and units based on classification, clustering, and topic modeling using digital footprints (Jira, meetings, emails, etc.)
• We conduct comprehensive effectiveness analysis as part of scenario modeling for activities aimed at achieving the bank management's goals.
• We implement pipelines for processing internal documents of arbitrary length to build recommendations for working with them and accelerating organizational changes.
• We identify global trends and analyze their impact on the headcount of the bank's roles for Sber's Strategy.
• We analyze organizational goal graphs (connectivity, cascading) and recommend ambitious goals considering the context and priorities of the Strategy.
• We expand the domain adaptation direction for improving streams of semantic search, ranking, and other NLP downstream tasks.
• We participate in the development of the global AI agents direction and regularly use modern LLM-based approaches in our work (External Tools, Reasoning, Reflection).
• We test hypotheses of any complexity to obtain Data-driven insights for preparing strategic sessions for the bank's management.
Our Global Priorities:
• Development and implementation of AI solutions (Classic NLP, LLM applications, AI agents) to enhance the efficiency of the bank's priority strategic processes with potential for use on the external market.
• Creating SotA (State-of-the-Art) solutions considering the specifics of the bank.
Why Choose Us:
• Opportunity to use cutting-edge AI technologies and the bank's platforms.
• Participation in the development of innovative services for the strategic unit, which bring real value to the processes and products of the entire bank and quickly come to the attention of key managers.
• Opportunity to participate in international projects and conferences on AI and ML.
• Working in a friendly team of professionals focused on achieving the most ambitious goals and constant development.
• Adaptation and training of language models based on internal and external data (Prompt Tuning, RAG, PEFT, SFT).
• Full cycle of data preparation for model training.
• Development and implementation of AI services (Classic NLP, LLM applications, AI agents, dialog systems) from the MVP stage to PROD (CRISP-DM).
• Interaction with business customers to identify requirements and independent task formulation.
• Participation in model validation and auto-monitoring, conducting A/B testing.
• Degree from a technical university in computer science, applied mathematics, or informatics. Most preferred: MIPT, MSU, Skoltech, HSE.
• Experience in fine-tuning LLMs using adapters.
• Understanding of the model lifecycle (CRISP-DM).
• Ability to translate a business problem statement into an ML problem statement, correct interpretation of obtained results.
• High proficiency in core Python.
• Knowledge of frameworks and libraries: PyTorch, Transformers.
• Knowledge of neural network architectures: RNN, LSTM, transformers (BERT, BART, T5).
• Knowledge of frameworks for working with LLMs (LangChain/GigaChain, LangServe/GigaServe, LlamaIndex, etc.).
• Containerization: Docker, OpenShift.
• Experience in writing scientific articles.
• Flexible hybrid schedule (discussed individually).
• Modern IT office near Moscow City with a fitness hall.
• Mortgage with benefits for employees and preferential lending terms.
• Free SberPrime+ subscription.
• Discounts on products from partner companies.
• Private health insurance from day one and preferential insurance for family members.
• Corporate pension program.
• Company-paid training: online courses at Sber's online school and unlimited access to the library, training at the Corporate University, workshops, meetups, and the opportunity to gain new qualifications.
• Largest DS&AI Community – over 600 DS specialists from the bank, regular knowledge sharing, experience and best practices exchange, interactive lectures and master classes from leading universities and experts of technology companies, digest on the latest developments in DS&AI and reports from the world's largest conferences.