Data Science Specialist (LLM)

Quick Facts

• Role focused on ML/LLM modeling, LLM solution development, and productionization (*MLOps/LLMOps*)
• Cross-functional collaboration and business-value-driven evaluation

Description

Work with cross-functional teams to apply advanced AI/ML methods to business needs. Design, deploy, and optimize machine learning models and build LLM-based solutions including text data preparation and model fine-tuning. Develop internal feature store and vector database capabilities and manage the ML/LLMOps lifecycle with performance monitoring tied to quality and business value.

Responsibilities

• Collaborate closely with teams across the organization to support business strategy using advanced data techniques
• Design, implement, and optimize ML models and integrate them with existing systems
• Build LLM solutions: prepare large text datasets for large language models and fine-tune existing models for specific needs
• Develop an internal feature store and vector database
• Manage the full ML model lifecycle and build an internal MLOps/LLMOps ecosystem
• Monitor algorithm performance using both quality metrics and generated business value

Requirements

• Relevant academic background in AI/ML (Math, Statistics, Computer Science or related)
• AI/ML engineering experience in an environment using agile methodologies
• Practical experience across the full lifecycle of AI/ML solutions (design, deployment, maintenance)
• Hands-on knowledge of ML algorithms (supervised/unsupervised learning, neural networks, regression, classification, segmentation, NLP)
• Experience with vector databases and LLMs, including fine-tuning, optimization, and version control
• Proficiency in Python and AI/ML libraries (pandas, numpy, scikit-learn, tensorflow/pytorch, xgboost, nltk, pyspark, Hugging Face, langchain)
• Strong SQL skills and Git version control
• Experience with cloud environments and big data processing
• Strong communication skills with the ability to explain complex solutions to different stakeholders
• English at least B2

Benefits

• Stable employment under an employment contract
• Hybrid work model (office visits 1–2 days per week)
• Annual bonus
• Wellbeing and development support (wellbeing platforms, online training, and foreign language learning)
• Cafeteria-style benefits (sport activity funding, private medical care, prepaid cards, and shopping discounts/vouchers)
• Company culture based on community, simplicity, client-first, responsibility, and trust