Key Responsibilities - Develop end‑to‑end NLP and GenAI solutions, including text classification, summarization, RAG systems, conversational AI, and document intelligence pipelines. - Build, fine‑tune, and evaluate LLM-based models using transformer architectures (BERT, GPT, T5, LLaMA, etc.). - Design and implement custom NLP workflows, embeddings, semantic search, vector databases, and prompt engineering strategies. - Develop scalable advanced ML models leveraging deep learning, traditional ML, and hybrid architectures. - Deploy models and AI apps using modern MLOps practices across cloud environments (Azure preferred). - Collaborate closely with product, engineering, and business teams to translate requirements into AI-driven solutions. - Monitor model performance, conduct error analysis, and continuously optimize pipelines.   Required Skills - 5–8 years of experience in data science with deep hands‑on expertise in NLP and Generative AI. - Proficient in transformer models, embeddings, and modern NLP libraries (Hugging Face, spaCy, NLTK). - Strong Python skills with experience in PyTorch/TensorFlow for advanced model development. - Practical experience building RAG architectures, vector search, and prompt optimization. - Solid understanding of MLOps, model deployment, monitoring, and productionization. - Strong problem‑solving abilities with excellent communication and stakeholder engagement skills.

Key Responsibilities - Develop end‑to‑end NLP and GenAI solutions, including text classification, summarization, RAG systems, conversational AI, and document intelligence pipelines. - Build, fine‑tune, and evaluate LLM-based models using transformer architectures (BERT, GPT, T5, LLaMA, etc.). - Design and implement custom NLP workflows, embeddings, semantic search, vector databases, and prompt engineering strategies. - Develop scalable advanced ML models leveraging deep learning, traditional ML, and hybrid architectures. - Deploy models and AI apps using modern MLOps practices across cloud environments (Azure preferred). - Collaborate closely with product, engineering, and business teams to translate requirements into AI-driven solutions. - Monitor model performance, conduct error analysis, and continuously optimize pipelines.   Required Skills - 5–8 years of experience in data science with deep hands‑on expertise in NLP and Generative AI. - Proficient in transformer models, embeddings, and modern NLP libraries (Hugging Face, spaCy, NLTK). - Strong Python skills with experience in PyTorch/TensorFlow for advanced model development. - Practical experience building RAG architectures, vector search, and prompt optimization. - Solid understanding of MLOps, model deployment, monitoring, and productionization. - Strong problem‑solving abilities with excellent communication and stakeholder engagement skills.

• Responsible for turning data into actionable insights and automations that enhance revenue generation and the efficiency of Go-to-Market strategies. • Develops and maintains analytical models, dashboards, and automated contact workflows, ensuring data quality, metric consistency, and strategic support for Product, Marketing, and Sales. • Conduct analyses and build automations that link customer behavior to product performance, enabling fast, accurate decisions about monetization, engagement, and retention. • Support leadership and Product Managers in managing key revenue indicators and designing conversion strategies to maximize value per customer and per product.

• Implement a machine learning algorithm that creates floorplan layouts automatically inside a given shape • participating in the creation of a tool that changes the way we build new flats • creating research road maps with budgeting • staying up to date with state of the art machine learning technology • conducting research that will lead to improvement of algorithms currently being used • develop quantitative benchmarks that will help evaluate quality of algorithms • proactively seek opportunities to improve various aspects of our business by applying scientific approach