Senior Data Scientist – Generative AI / LLM Specialist

O projekcie: We are looking for a Data Scientist to join our AI team and support clients in building end-to-end Talk-To-Data (TTD) solutions powered by LLMs and GenAI models. The AI team focuses on cutting-edge aspects of Generative AI and LLMs with applications such as RAG, summarization, multi-agent workflows, and model fine-tuning. With deep, PhD-level expertise in GenAI, NLP, and Computer Vision, this is an excellent environment for professionals eager to push their skills to new heights. We are seeking candidates for long-term engagement in GenAI and related domains. Wymagania: - Solid understanding of deep learning concepts. - Experience in Machine Learning, particularly in Generative AI (LLM/LMM), with focus on NLP or multimodal models. - Experience gathering business requirements and translating them into technical plans, data processing, feature engineering, model evaluation, hypothesis testing, and model deployment. - Strong Python and object-oriented programming skills; working knowledge of SQL and vector databases. - Experience with Azure or GCP cloud platforms. - Knowledge of Deep Learning and GenAI libraries: NumPy, PyTorch, HuggingFace, LangChain, LangGraph, and GenAI APIs (OpenAI, Gemini). - Hands-on experience designing or operating MCP servers/clients for LLM agents. Nice to Have - Experience working with Databricks. - Proven commercial experience in Generative AI, NLP, or Computer Vision projects. - Familiarity with microservice architectures. - Experience with code repositories and code assistants. - Strong business acumen and ability to propose creative solutions for client problems. - Ability to mentor and lead junior team members. Codzienne zadania: - Develop end-to-end GenAI applications such as chatbots, voicebots, and Talk-to-Data systems, including data ingestion, retrieval layers, orchestration (e.g., LangChain, LlamaIndex, LangGraph), API/backend, and simple UI where needed. - Design and implement RAG pipelines with vector databases, hybrid search, rerankers, query transformation, and evaluation frameworks for relevance and robustness. - Perform model selection, prompting strategies, and fine-tuning (LoRA/QLoRA/SFT) for text, code, and multimodal models, including guardrails, output evaluation, and A/B testing. - Design, integrate, and optimize LLM interactions with external tools, APIs, and data sources using Model Context Protocol (MCP) connectors. - Understand business requirements and translate them into technical goals, define success metrics, audit data feasibility, and align stakeholder expectations. - Support project delivery and pre-sales initiatives.