6 дней назад
Middle Python Developer (ML)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Middle Python Developer (ML) (AI/RAG): Design and implement LLM-based features and RAG pipelines for intelligent search, question answering, and enterprise knowledge structuring with an accent on Python, vector embeddings, hybrid search, and information processing. Focus on evaluating model quality, tuning retrieval relevance, integrating AI components into production platforms, and owning delivery from design through deployment.
Location: Europe, Albania, Poland, Romania, or Ukraine
Company
Software engineering company delivering technology solutions for international customers, including large-scale telecommunications and AI initiatives.
What you will do
- Design and implement LLM-based features and RAG pipelines from data ingestion through answer generation.
- Build and optimize retrieval using vector embeddings, hybrid semantic search, and keyword search.
- Process, clean, and structure source information through data preparation, chunking, metadata enrichment, and relevance tuning.
- Evaluate model quality, experiment with new approaches, and move proven solutions into production.
- Integrate AI components into the wider platform and own changes through design, implementation, testing, and deployment.
- Work independently while communicating blockers, scope questions, and technical trade-offs.
Requirements
- 3+ years of commercial software development experience.
- 2+ years of experience working on AI/ML projects.
- Hands-on Python development experience.
- Practical experience with LLMs, RAG architecture, vector embeddings, and hybrid search.
- Experience improving AI output quality through information processing and relevance tuning.
- Upper-Intermediate English required.
Nice to have
- Experience with knowledge graphs or graph databases.
- Background in telecommunications.
Culture & Benefits
- Work independently and take ownership of tasks from design through deployment.
- Collaborate with a team integrating AI components into broader platform capabilities.
- Choose between an LLM-powered technical documentation assistant and a knowledge graph platform initiative.
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