Data Scientist

Commit Offshore is seeking an experienced Mid/Mid+ Data Scientist to design, develop, and optimize Large Language Models for various NLP tasks. The ideal candidate will have strong expertise in LLMs such as GPT and Claude, with a background in natural language processing and deep learning. They will play a critical role in developing and deploying cutting-edge LLM applications to drive innovation across product lines.

• Design, develop and optimize Large Language Models for NLP tasks such as text generation, summarization, translation, and question-answering
• Conduct research and experiments to push the boundaries of LLM capabilities and performance
• Collaborate with cross-functional teams (engineering, product, research) to integrate LLMs into product offerings
• Develop tools, pipelines and infrastructure to streamline LLM training, deployment and monitoring
• Analyze and interpret model outputs, investigate errors/anomalies, and implement strategies to improve accuracy
• Stay current with the latest advancements in LLMs, NLP and machine learning research
• Communicate complex technical concepts to both technical and non-technical stakeholders

• MS or PhD degree in Computer Science, Data Science, AI, or a related quantitative field
• 2-3+ years of hands-on experience developing and working with deep learning models, especially in NLP/LLMs
• Expert knowledge of Python, PyTorch, TensorFlow, and common deep learning libraries
• Strong understanding of language models, attention mechanisms, transformers, sequence-to-sequence modeling
• Experience training and fine-tuning large language models
• Experience with classical ML models - XGBoost, LightGBM
• Proficiency in model deployment, optimization, scaling and serving
• Excellent problem-solving, analytical and quantitative abilities
• Strong communication skills to present technical information clearly
• Ability to work collaboratively in a team environment
• Fluency in Ukrainian and English

Preferred qualifications include research experience in LLMs and NLP, experience working with multi-modal data (text, image, audio), knowledge of cloud platforms like AWS and GCP for model training, understanding of MLOps and production ML workflows, and background in information retrieval, knowledge graphs, and reasoning.