Nlp Software Engineer

About the Role

NLP Engineer

Key Responsibilities

• Design, develop, and implement NLP models and algorithms for text processing, classification, sentiment analysis, entity recognition, question answering, summarization, and more.
  
• Preprocess and analyze large volumes of unstructured text data using tokenization, parsing, stemming, lemmatization, and embedding techniques.
  
• Fine-tune and deploy pre-trained language models such as BERT, GPT, RoBERTa, or other transformer-based architectures.
  
• Collaborate with data scientists, software engineers, and product teams to integrate NLP capabilities into applications and services.
  
• Optimize NLP models for performance, scalability, and real-time inference.
  
• Conduct research on state-of-the-art NLP techniques and stay updated with academic and industry trends.
  
• Prepare and maintain technical documentation and reports.
  
• Participate in code reviews, testing, and model evaluation to ensure quality and robustness.
  
• Work with cloud platforms and containerization tools for deployment (AWS, GCP, Azure, Docker, Kubernetes).
  

Qualifications

• Bachelors or Master’s degree in

  Computer Science, Computational Linguistics, Artificial Intelligence, or related field

  .
• 2+ years of experience in developing NLP models or working on natural language processing projects.
  
• Strong programming skills in

  Python

  , with proficiency in libraries like

  NLTK, SpaCy, Transformers (Hugging Face), TensorFlow, PyTorch

  .
• Experience with machine learning and deep learning techniques applied to NLP tasks.
  
• Familiarity with text embedding methods such as

  Word2Vec, GloVe, FastText, or contextual embeddings

  .
• Understanding of linguistic concepts such as syntax, semantics, and pragmatics.
  
• Knowledge of evaluation metrics for NLP models (accuracy, F1, BLEU, ROUGE, perplexity).
  
• Experience with data cleaning, feature engineering, and handling large datasets.
  

Preferred Skills

• Experience with

  cloud-based ML platforms

  (AWS SageMaker, Google AI Platform, Azure ML).
• Familiarity with

  transformer architectures

  and recent advances in NLP research.
• Background in

  information retrieval

  ,

  dialogue systems

  , or

  speech processing

  is a plus.
• Experience in deploying models using REST APIs or microservices architecture.
  
• Knowledge of container orchestration (Docker, Kubernetes).
  
• Publications or contributions to NLP conferences/journals or open-source projects are a bonus.
  

Soft Skills

• Strong analytical and problem-solving mindset.
  
• Effective communication and teamwork skills.
  
• Self-motivated with a passion for research and innovation.
  
• Detail-oriented and quality-focused.
  
• Ability to manage multiple projects and priorities in a dynamic environment.