Description
The team is engaged in developing AI agents and ML models that predict deterioration in a client's financial condition, using transactional, financial, and diverse external data.
There is already a working product, as well as several promising developments that need to be advanced.
The team supports the full lifecycle of models (from business idea to putting a model into industrial operation).
Responsibilities
- implementing AI agents into the bank's industrial framework
- industrializing prototypes, reviewing, and optimizing code for classic ML models (on Python + Spark stack) for batch and online execution
- solving problems when deploying agents and models to production
- investigating incidents during the operation of agents and models.
Requirements
- knowledge of Python (including numpy, pandas, pyspark, OOP, testing, etc.). Knowledge of asynchronous programming is a separate plus.
- knowledge of SQL (all basic operations, understanding of window functions), joins, aggregates, window functions
- proficiency in CI/CD tools (jenkins, git, etc.)
- work experience with Spark
- experience in turning prototypes into industrial code
Conditions
- comfortable, modern office near Kutuzovskaya metro station
- hybrid work format
- annual salary review and annual bonus
- corporate gym and relaxation areas
- more than 400 educational programs from SberUniversity for professional and career development
- extended voluntary health insurance, preferential insurance for family
- flexible mortgage discount equal to 1/3 of the Central Bank's key rate
- free SberPrime+ subscription, discounts on products from partner companies
- referral bonus for recommending friends to the Sber team.
