Paid internship in Sber's B2B AI transformation team. In 3 months, you will dive into the design of LLM-based agent systems with the opportunity to receive an offer for a junior position.
Tasks:
- study LLM agent design patterns
- master the LangChain, LangGraph, and internal AEF SDK stacks
- design the architecture of LLM-based AI agents
- develop agent systems: ReAct, Plan-and-Execute, Multi-Agent
- integrate agents with internal APIs and banking systems
- develop and improve RAG pipelines
- participate in the industrial implementation of agent solutions
- evaluate agent quality: metrics, testing, reliability, behavioral stability
Requirements:
- you are in your final year of master's studies, have already completed a master's degree, or are studying for a PhD
- you have a strong mathematical, technical, or engineering background
- you write confidently in Python
- you can quickly learn new libraries, frameworks, and approaches
- you are ready to dive deep into solution architecture
Conditions:
- paid internship
- work with real business tasks
- immersion in the design of LLM agents and agent systems
- access to internal stack and tools
- unlimited GigaCode developer agent tariff
- opportunity to receive an offer for a Junior Data Scientist / Junior AI Engineer position upon completion of the internship
Skills:
- Python
- LangChain
- LangGraph
- AEF SDK
- RAG
- FAISS
- Chroma
- Qdrant
- Llama
- Mistral
- Qwen
- MLP
- CNN
- RNN
- LSTM
- Transformers
- ML
- MLOps
- DevOps
- API
- CI/CD
- containerization
