NLP Research Scientist / NLP Research Analyst

Role Description The NLP Research Scientist / NLP Research Analyst is responsible for researching, developing, and evaluating natural language processing (NLP) models and language-based AI systems. The role focuses on advancing language understanding, text generation, conversational AI, and linguistic intelligence capabilities to support AI-driven products and research initiatives. Key responsibilities include conducting experiments on NLP models, developing algorithms for language understanding and generation, and analyzing large-scale text datasets. The role involves working on applications such as chatbots, search systems, machine translation, summarization, sentiment analysis, question answering, and large language model (LLM) optimization. The NLP research professional works closely with machine learning engineers, AI scientists, product teams, and data engineers to design scalable NLP solutions and improve model performance. They are responsible for building evaluation frameworks, fine-tuning language models, and publishing or documenting research findings. In addition, the role includes exploring emerging NLP techniques, benchmarking models, improving model efficiency, and ensuring responsible AI practices related to fairness, bias mitigation, and safety. The NLP Research Scientist / NLP Research Analyst plays a key role in advancing language AI capabilities and enabling intelligent human-computer interaction. Qualifications Bachelor’s, Master’s, or PhD in Computer Science, Artificial Intelligence, Computational Linguistics, Data Science, Mathematics, or a related field 2–10+ years of experience in NLP research, machine learning, AI engineering, or data science roles Strong understanding of NLP concepts, transformer architectures, and large language models (LLMs) Experience with machine learning and deep learning frameworks such as PyTorch, TensorFlow, Hugging Face, or similar tools Strong programming skills in Python and experience handling large-scale text datasets Familiarity with NLP tasks such as text classification, entity recognition, summarization, embeddings, and conversational AI Experience with model evaluation, experimentation, and statistical analysis Strong analytical, mathematical, and research-oriented problem-solving skills Familiarity with distributed training, vector databases, or retrieval systems is an advantage Strong communication and technical documentation abilities Experience publishing research papers or contributing to open-source AI projects is a plus Knowledge of responsible AI, model safety, and bias mitigation practices is highly preferred