at MTS remotely
ML Engineer/Python Developer for the SmartDocs MTS team: creating RAG systems and AI agents, working with documents, designing microservices and databases.
Tasks:
- Design microservices and APIs (REST/gRPC)
- Create RAG and AI agents: develop systems for generating responses based on documents, chains of thought, and Tool Calling logic (LangChain/LangGraph/LlamaIndex)
- Work with data and text: parsing, cleaning, and chunking texts, entity extraction (NER), classification, implementation of hybrid semantic and full-text search
- Design databases: work with relational (PostgreSQL), vector (Qdrant/Milvus/pgvector), and graph (Neo4j) databases for GraphRAG tasks
- Optimize performance, cover code with tests (Pytest), write asynchronous code in Python (FastAPI/Django)
- Conduct code reviews and application containerization (Docker)
Requirements:
- 2+ years of commercial Python development experience for graduates of specialized faculties of leading universities (MSFTI, HSE, MSU, ITMO, MSTU. Bauman, SPbSU, MEPhI) or 3+ years for candidates with other education
- Solid knowledge of Python, asynchronous programming, web frameworks (FastAPI), and microservice architecture design principles (REST, Swagger, gRPC)
- Practical experience with LangChain, LlamaIndex, LangGraph, modern LLMs (GPT, open-source models), and frameworks for creating AI agents
- Experience in processing and classifying documents of various formats (PDF, scans), entity extraction (NER, hybrid search) using Transformers, BERT, SpaCy, Natasha
- Experience with relational DBs (PostgreSQL), NoSQL/caching (Redis), vector DBs (Qdrant/Milvus/pgvector), and graph systems (Neo4j)
- Experience with message brokers (RabbitMQ, Kafka)
- Proficiency in containerization and CI/CD tools (Docker, Git, S3)
- Understanding of the full software development lifecycle (SDLC)
- Experience working with technical specifications, reading diagrams (UML, BPMN)
