Software Engineer

R&D and pipelines: Design the architecture for transforming input data into a presentation structure (sections, slides, text, visuals). GenAI and LLM: Configure and experiment with LLMs and multimodal models for content generation. Prototyping: Develop service prototypes in conjunction with the backend team, participate in API design. Quality Assessment: Formulate metrics and quality criteria for generation (readability, completeness, compliance with technical specifications). Knowledge Sharing: Document approaches, limitations, and best practices for working with the service.

Requirements

Experience: 3+ years in DS/ML, mandatory experience working with generative models. Stack: Proficient Python, PyTorch, classic ML stack (pandas, scikit-learn, NumPy). GenAI expertise: Deep understanding of how LLMs work: from prompt engineering, RAG, and agents to PEFT, KV-cache, MCP/Tool calling. Infrastructure: Understanding of the principles of building ML services (Docker, REST API, on-prem environments). Soft skills: Ability to translate experiments into working prototypes, effective communication with developers and analysts. Language: English (fluent reading of technical documentation).

Higher education — Bachelor's degree; Experience: 3 years