Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.
About the role and client: We’re looking for a Machine Learning Engineer to develop applied AI and agentic tools. Our client is building an advanced AI assistant that helps teams work smarter. By combining semantic search, agentic AI, and state-of-the-art language models, the system enhances internal operations through intelligent, context-aware support and personalized interactions.
Requirements: — Strong proficiency in Python; — Experience with agentic AI frameworks such as LangChain or LangGraph; — Solid understanding of machine learning and NLP fundamentals; — Hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow); — Familiarity with prototyping tools such as Streamlit or Gradio; — Knowledge of engineering best practices: Git, Docker, cloud basics, and task estimation; — Practical knowledge of SQL; — Upper-Intermediate level of English (both written and spoken).
Would be a plus: — Experience with other agentic or LLM orchestration tools; — Experience with MLOps or model deployment; — Comfortable working in Linux terminal environments.
Responsibilities: — Develop and integrate ML and NLP models to power intelligent assistant features; — Build agentic workflows using LangChain, LangGraph, or similar frameworks; — Prototype user interfaces and internal tools using Streamlit or Gradio; — Collaborate with the engineering and product teams to plan and deliver ML-driven features; — Work with Docker to manage development and runtime environments; — Use Git for version control and write clean, maintainable code; — Query structured data using SQL; — Contribute to model deployment and operations in a cloud environment (primarily Azure).
