💼IT Center at Bauman Moscow State Technical University💼

Position: Engineer/ Data Scientist LLM Grade: Middle/ Senior Location: Russian Federation, Moscow, Moscow Oblast Employment: full-time Work Format: hybrid/remote for residents of Moscow and Moscow Oblast Employment Contract: Labor Code of the Russian Federation Salary: discussed based on interview results Bonus: Opportunity for additional training in advanced qualification programs. Contact: @Tatiana654321

📌About Us: We develop and implement large-scale projects using artificial intelligence for major federal clients, implement development projects for the commercial sector, as well as knowledge-intensive projects.

📗Tasks:

✔️ Design and implement LLM solutions for applied scenarios: QA assistants, document search, analytical assistants, classification/entity extraction, etc. (main focus — NLP/LLM). ✔️ Build RAG pipelines: data preparation and chunking, indexing, retrieval (including with filters), reranking, answer generation, handling “no answer”. ✔️** Adapt models to the domain:** prompt engineering, SFT/LoRA (or other fine-tuning approaches), dataset selection/labeling, error analysis and iterations. ✔️ Develop and maintain agent scenarios: function calling, tool-use, step orchestration, control of limitations/policies, exception handling, reliability assessment. ✔️ Establish quality evaluation: offline metrics, test sets, human evaluation protocols, interpretation of results and improvement plan. ✔️ Participate in production deployment: prototype → service → monitoring of quality/latency/cost, participation in degradation and regression analysis. ✔️ Quickly understand documentation/repositories and propose solutions based on best practices and infrastructure limitations. ✔️** Team management**, training and mentoring junior and new employees.

📕What we expect from you:

✔️ Higher technical education in IT and / or advanced training in Data Science. ✔️ Proficiency in Python and core ML libraries (Pandas, Sklearn, Tensorflow, Keras, PyTorch, XGBoost or similar). ✔️ Understanding of classical ML and basic neural network architectures; ability to select metrics and interpret results. ✔️ Experience with NLP libraries: pymorphy2, NLTK, spaCy, regex. ✔️ Experience with LLM, prompt-engineering, fine-tuning, RAG, MCP. ✔️ Experience with Hugging Face Transformers. ✔️ Experience with vLLM. ✔️ Experience with vector databases (Qdrant or similar).

🔥If interested – write: @Tatiana654321