Intern Engineer for the Machine Learning Development team at Sberbank's Center for Practical Artificial Intelligence. Participation in the development of LLM-based agent systems for working with banking data – from prototype to implementation.
Tasks:
- Develop PoC and MVP of AI agents based on LLM using frameworks (LangChain, GigaChain)
- Analyze and adapt existing SOTA practices
- Participate in the full development and integration cycle: from creating prototypes to production implementation and monitoring of solutions
- Interact with applied and business teams within the Sber ecosystem
Requirements:
- Current study in the final years of Bachelor's, Master's, or PhD programs at a technical university with a strong foundation in mathematics and algorithms
- Proficient knowledge of Python (NumPy, Pandas, PyTorch, OOP basics, etc.)
- Deep understanding of Deep Learning (DL) and classical Machine Learning (ML)
- Practical experience with LLMs, RAG, and relevant frameworks and databases (LangChain, FAISS, Qdrant), and a desire to grow in this field
- Experience with development tools (bash, git), including experience in team development or a willingness to quickly acquire these skills
- Ability to understand scientific publications and modern SOTA solutions, formulate and promote own research hypotheses
Conditions:
- Paid internship
- Internship duration: 3 months: 40 hours per week, 9:00 to 18:00; or 6 months: 20 hours per week, 9:00 to 18:00
- Hybrid work format with office visits at least 3 days a week
- Comfortable modern office at the address: Moscow, Kutuzovsky Prospekt, 32
- Professional team (our center includes PhDs, postgraduates, and Kaggle Masters)
- Interesting tasks and active work with new technologies
Skills:
- Python
- NumPy
- Pandas
- PyTorch
- LLM
- RAG
- LangChain
- GigaChain
- FAISS
- Qdrant
- bash
- git
- DL
- ML
