About the Role :
We are looking for a skilled and innovative Natural Language Processing (NLP) Engineer to join our AI / ML team. In this role, you will build, train, and optimize language models and NLP systems that power real-world applications such as chatbots, document analysis, semantic search, recommendation systems, and more.
As an NLP Engineer, youll work on state-of-the-art language technologies including transformer models, large language models (LLMs), and domain-specific NLP pipelines.
Key Responsibilities :
- Develop and deploy NLP models for tasks such as text classification, named entity recognition (NER), sentiment analysis, question answering, and summarization.
- Fine-tune and evaluate transformer-based models (e.g., BERT, GPT, RoBERTa, T5) on domain-specific tasks.
- Work with large-scale datasets to preprocess, clean, and tokenize text data effectively.
- Implement NLP pipelines and services for integration into production systems.
- Collaborate with data scientists, software engineers, and product teams to define and meet project goals.
- Monitor model performance and iterate on improvements using metrics and user feedback.
- Stay updated on the latest NLP research and incorporate new techniques where appropriate.
Required Qualifications :
Bachelors or Masters degree in Computer Science, Computational Linguistics, Artificial Intelligence, or a related field.Solid hands-on experience with Python and key NLP libraries (e.g., Hugging Face Transformers, SpaCy, NLTK, Gensim).Strong understanding of machine learning fundamentals, especially in NLP applications.Experience with deep learning frameworks like PyTorch or TensorFlow.Familiarity with deploying models as APIs or services (e.g., using Flask, FastAPI, Docker).Knowledge of common NLP evaluation metrics (e.g., F1, BLEU, ROUGE, perplexity).Preferred Qualifications :
Experience with large language models (LLMs) and prompt engineering.Prior work in a specific domain such as healthcare, legal, or finance NLP.Experience with vector search technologies (e.g., FAISS, Pinecone, Elasticsearch).Familiarity with multi-lingual or cross-lingual NLP techniques.Contributions to open-source NLP projects or publications in NLP / AI conferences (e.g., ACL, EMNLP, NAACL).(ref : hirist.tech)