We are looking for Data Scientists for the "People and Culture" Block with a specialization in solving problems in the fields of AI agents, LLM, RecSys, NLP, Classic ML.
What tools do we use:
Standard stack: Python (JupyterLab) + PostgreSQL (GreenPlum).
The team works with tasks such as:
- implementation of multi-agent systems (GigaChat + RAG + API), such as the HRS platform agent orchestrator, handling employee inquiries, etc.
- creation of multimodal recommendation systems
- classic ML models for forecasting and ranking
- fine-tuning embeddings and other tasks that help make Sber's HR processes better.
The first stage of selection for this vacancy is an interview with an AI recruiter. After applying, you will receive an invitation to your email and chat on the HeadHunter platform to undergo a preliminary interview with GigaRecruiter in Telegram. The dialogue will take approximately 10 minutes. Its task is to clarify missing details and speed up the review of your candidacy.
GigaRecruiter is just starting its journey, so we ask for your understanding. Your experience and participation will help make it convenient and useful!
Responsibilities
- analysis of business requirements and formalized description of the modeled business process with business stakeholders
- analysis of the business task and proposal of modeling methods to solve the business task
- development of model architecture and prototype creation
- deployment of the model into industrial operation together with the MLOps team
- development of documentation for the model
- model support during industrial operation.
- determination of data needs and readiness
- confirmation of data requirements for proceeding to model creation
- determination of requirements for the list, volume, and quality of data necessary for solving the business task.
Requirements
- at least 2 years of experience in DS
- confident Python programming and SQL knowledge
- understanding of LLM and multi-agent systems operation
- knowledge of the ML, DL stack of Python and key libraries, numpy, pandas, pytorch, LightGBM
- team experience and knowledge of collaborative development tools (git, jira, etc.).
Will be a plus:
- experience with the Big Data stack (GreenPlum, Hadoop).
Conditions
- comfortable modern office near Kutuzovskaya metro station
- hybrid format
- annual salary review and annual bonus
- corporate gym and rest areas
- unique Sber training system for professional and career development
- extended voluntary medical insurance, preferential insurance for family and corporate pension program
- free SberPrime+ subscription, discounts on products from partner companies
- reward for recommending friends to the Sber team.
