NLP Engineer - Artificial Intelligence/Machine Learning

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).