Senior Data Science Engineer (ML)

TL;DR

Senior Data Science Engineer (ML/LLM): Design and improve ML and LLM-powered solutions for content personalization, recipe recommendations, and SEO features with an accent on retrieval, ranking, and evaluation frameworks. Focus on building scalable data pipelines, monitoring model performance, and translating business needs into production-ready AI systems.

Wroclaw, Poland

Company

Global leader in the meal kit delivery industry, building intelligent ML-driven experiences for digital platforms.

What you will do

• Design and improve ML and LLM-powered solutions for content personalization and customer experiences
• Build scalable data pipelines for processing and transforming large-scale text data
• Develop retrieval, ranking, and recommendation systems to improve content quality and relevance
• Design evaluation frameworks for LLM outputs, including quality, safety, and performance metrics
• Monitor model performance and business impact through experiments, dashboards, and data analysis
• Collaborate with cross-functional teams to translate business needs into production-ready ML solutions
• Take ownership of features and initiatives from idea to launch

Requirements

• Strong experience with LLM evaluation frameworks, including human review, automated checks, and quality evaluation (safety, tone, factuality)
• Solid understanding of retrieval and ranking metrics (Hit@K, Recall@K, Precision@K) and performance measurement principles
• Strong SQL skills and experience building dashboards and analytical views in Databricks or lakehouse environments
• Strong Python skills for scalable data pipelines and large-scale text processing
• Experience with embeddings and semantic similarity techniques, including clustering and duplicate detection
• Strong experimentation mindset with experience in monitoring, measurement, and model performance evaluation
• Ability to translate ML decisions into business impact and product outcomes
• Strong ownership, adaptability, and ability to work effectively in ambiguous environments
• Strong communication skills and proactive approach

Nice to have

• Experience with SEO and product analytics concepts
• Experience with multilingual NLP
• Knowledge of graph algorithms and clustering techniques
• Experience with reranking approaches and semantic search optimization
• LLM calibration and evaluation tuning experience
• Hands-on experience with MLOps and production ML environments (Databricks, MLflow, batch inference, etc.)
• Experience with content safety and governance workflows
• Experience designing human-in-the-loop review and approval processes

Culture & Benefits

• Paid Vacation
• Sick Days
• Sport/Insurance Compensation
• English Classes
• Charity
• Training Compensation