Mid / Mid+ Data Scientist (LLMs & NLP) (Remote)

We are looking for an experienced Data Scientist specializing in Large Language Models (LLMs) to join our fast-growing team. You will work with state-of-the-art models such as GPT and Claude, driving applied research and real-world product delivery. This role is ideal for someone passionate about NLP, deep learning, and pushing the limits of generative AI. Details * Location: Remote (Ukraine or EU-friendly time zones) * Employment Type: Full-time, Contract * Start Date: ASAP * Language Requirements: Ukrainian & English (fluent) Key Responsibilities * Design, develop, and optimize LLMs for NLP use cases: text generation, summarization, translation, Q&A. * Conduct applied research and experiments to extend LLM performance and capabilities. * Collaborate with engineering, product, and research teams to integrate LLMs into production systems. * Build and maintain pipelines, tools, and infrastructure for training, fine-tuning, deploying, and monitoring LLMs. * Analyze model results

troubleshoot errors, and implement accuracy and performance improvements. * Stay up-to-date with cutting-edge AI/ML breakthroughs and evaluate their relevance for the product. * Explain complex concepts clearly to both technical and non-technical stakeholders. Requirements * MS or PhD in Computer Science, Data Science, AI, Mathematics, or related field. * 4+ years of hands-on experience with deep learning, particularly NLP and transformers. * Strong expertise in Python, PyTorch, TensorFlow, and modern deep learning frameworks. * Deep understanding of LLM architectures, attention mechanisms, transformers, and seq-to-seq models. * Experience training, fine-tuning, scaling, and deploying LLMs. * Practical knowledge of model optimization, inference, and serving. * Strong analytical mindset and problem-solving skills. * Excellent communication abilities and a teamwork mindset. * Fluency in Ukrainian and English. Nice to Have * Previous research experience in NLP, LLMs, or machine learning. * Experience with multi-modal data (text, audio, image). * Familiarity with AWS, GCP, or other cloud platforms for large-scale training. * Understanding of MLOps, production ML workflows, and monitoring. * Background in information retrieval, knowledge graphs, or reasoning models. #J-18808-Ljbffr