NLP Engineer

Job Description

Key Responsibilities:

• Develop and implement NLP models for text processing and understanding
• Build end-to-end NLP pipelines (data ingestion → preprocessing → modeling → deployment)
• Perform tasks such as intent classification, Named Entity Recognition (NER), and text summarization
• Train, evaluate, and fine-tune machine learning and deep learning models
• Develop APIs and backend services using FastAPI or Flask
• Work with large-scale structured and unstructured datasets
• Deploy and monitor models in production environments
• Collaborate with data scientists, engineers, and product teams

Good to Have:

• Experience with conversational AI frameworks like Rasa
• Knowledge of LLMs / Generative AI
• Exposure to cloud platforms (AWS, GCP, Azure)
• Experience with MLOps tools and pipelines
• Multilingual NLP experience

Programming:

• Strong proficiency in Python
• Experience writing clean, scalable, and production-ready code

NLP & Machine Learning:

• Solid understanding of NLP concepts: Tokenization, stemming, lemmatization
• POS tagging, parsing
• Word embeddings and transformers
• Hands-on experience with NLP libraries like spaCy and NLTK
• Experience with ML frameworks such as TensorFlow or PyTorch
• Familiarity with transformer models via Hugging Face Transformers

Backend & Deployment:

• Experience building APIs using FastAPI / Flask
• Understanding of RESTful services and microservices architecture
• Knowledge of Docker and deployment workflows

Education:

• Bachelor’s/Master’s degree in Computer Science, AI, Data Science, or related field

Soft Skills:

• Strong analytical and problem-solving abilities
• Effective communication skills
• Ability to work in collaborative, agile environments