Data Scientist (Python + GenAI)

Work model: Remote (+ occasional office work, during client visits)

Rate: 145 - 160 PLN/h Net + VAT

Start: ASAP

Project length: 12 months contracts + extensions

Project language: English, Polish

Workload: Full time

• Design and implement innovative AI and machine learning solutions for both internal and clients projects.
• Develop and validate intelligent assistants utilizing cutting-edge large language models such as GPT-4, Falcon 2, LLAMA 3, and Mixtral, incorporating Retrieval Augmented Generation (RAG) techniques and leveraging frameworks like Langraph and CrewAI.
• Provide expert guidance on technical strategies and solution architectures to address complex business challenges using AI.
• Simplify and present intricate technical concepts in a clear and actionable manner for both technical and non-technical stakeholders.
• Collect, preprocess, and analyze extensive datasets for training machine learning models.
• Contribute to documentation efforts and share industry best practices to enhance project outcomes.

• At least 4 years of relevant professional experience in AI or machine learning.
• Proven experience in building applications with Large Language Models (LLMs), utilizing techniques like RAG, vector databases, embeddings, and prompt engineering.
• Familiarity with LLM frameworks such as Langchain or LLamaindex.
• Advanced proficiency in Python programming.
• Strong understanding of statistics and its application in machine learning.
• Deep knowledge of machine learning and AI, including algorithm types, frameworks, model evaluation metrics, and AI architectures.
• Experience training and working with transformer-based models for text or image data.
• Expertise in managing and processing large datasets using tools like Pandas, NumPy, and SQL.
• A degree in a relevant field such as Economics, Computer Science, Mathematics, Physics, or related disciplines.
• Excellent English and Polish communication skills, both written and spoken.
• Exceptional analytical and problem-solving capabilities.

• Familiarity with GenAI agent frameworks and libraries like Langraph, CrewAI, Autogen, or Taskweave.
• Knowledge of Natural Language Processing (NLP) methods and techniques.
• Proficiency in additional programming languages such as C#, Go, or Java.
• Understanding of key concepts in reinforcement learning.