What is One Day Offer
The main idea of the event is to pass an interview and get a job offer in one day!
What we expect from candidates
We are looking for ML Engineers, Data Scientists, AQA, and Backend Developers with 3+ years of experience.
How the event will take place
By September 18 Apply
Pass the screening with a recruiter
September 19 Participate in team presentations, technical sessions, and finals
One Day Offer Schedule
- 10:00 AM — Team presentations
- 11:00 AM–4:00 PM — Technical sessions
- 4:00 PM–7:00 PM — Finals with the team
- 7:00 PM — Feedback
Which team are we hiring for
Sber's AI Construction
We are creating an ecosystem of AI agents for construction processes at Sber.
Our main activity is the end-to-end implementation of GenAI initiatives in the Construction Block: idea development, work and resource planning, AI agent development (change and disrupt), integration of AI agents into target automated systems, creation of an AI-Hub (PJSC and subsidiaries), creation of a PKAAP, hypothesis testing through pilot launches (research work), creation of local solutions for working with categorized information. Approving and applying autonomous agents of the Giga-assistant.
We need versatile engineers capable of managing features from database design to the implementation of complex interactive interfaces, with a deep understanding of AI agent implementation specifics. Team players with a high level of responsibility, proactivity, and a flexible approach to results-oriented work.
Our goal is to increase the efficiency of construction processes through automation and AI agentification.
Senior Data Scientist
- Development of ML solution architecture for autonomous agents.
- Specialization of fundamental models (LLM/Vision) for construction tasks.
- Building enterprise-grade RAG systems for information extraction from unstructured documents.
- Implementation of MLOps practices: quality monitoring, A/B testing, and deep optimization of latency/cost during inference.
Backend Developer
- Experience in Python development: 3+ years in commercial development, including writing high-load services.
- Web frameworks: deep knowledge of FastAPI and/or Django (RESTful API development, middleware, error handling, validation).
- Asynchronous programming: confident command of asyncio, aiohttp/httpx for working with external APIs and non-blocking operations.
- Database work: experience in schema design in PostgreSQL (including query optimization) and working with NoSQL (MongoDB, Redis for caching).
- Integration with AI/LLM: practical experience in calling and managing external APIs: understanding timeouts, retries, streaming.
- Understanding of microservice architecture, experience with message brokers (RabbitMQ or Kafka).
- Containerization and orchestration (Docker, Kubernetes — basic deployment and configuration skills).
- Familiarity with Pinecone, Weaviate, Qdrant, or Milvus (will be an advantage: ability to perform search, insertion, and manage indexes).
- Experience in writing unit and integration tests (pytest), understanding of TDD/BDD principles.
- CI/CD and monitoring: setting up pipelines (GitHub Actions/GitLab CI), basic knowledge of logging (ELK, Prometheus/Grafana).
- Knowledge of development processes: experience working in Agile teams (Scrum/Kanban), conducting code reviews, participating in sprint planning, ability to decompose tasks and estimate them.
QA Engineer
- Functional and regression testing of products with LLM components (web interfaces, APIs, integrations).
- Development and maintenance of test case sets for evaluating model response quality (evaluation datasets, golden sets).
- Prompt testing: checking robustness to paraphrasing, edge cases, injections, and jailbreaks.
- Evaluation of LLM responses based on criteria: accuracy, completeness, hallucinations, format compliance (structured output/JSON Schema).
- Reproduction of intermittent defects, statistical assessment of stability.
- Automation of routine checks in Python (pytest): smoke tests for APIs, running evaluation scenarios, scripts for mass checking model responses.
- Testing API integrations with LLM providers (OpenAI, Anthropic, OpenRouter, etc.): limits, retries, error handling, streaming.
Work Format
- Hybrid in Moscow, St. Petersburg, or Novosibirsk.
Benefits of working with us
- Annual salary review, annual bonus, flexible mortgage discount of 1/3 of the key rate of the Bank of Russia
- Extended VHI (Voluntary Medical Insurance), preferential insurance for family members, and a corporate pension program
- Over 400 educational programs from SberUniversity for professional and career development
- Corporate gym and rest areas, free SberPrime+ subscription, discounts on products from partner companies
- Referral bonus for recommending friends to the Sber team
About Sber
Industry: Banks / Fintech
Size: 1001+
Sberbank is the largest bank in Russia, Central and Eastern Europe, and one of the leading international financial institutions. The most valuable Russian brand and the strongest banking brand in the world according to Brand Finance.
