Scienaptic - NLP Engineer - Artificial Intelligence Solutions

Job Summary :

We are seeking a talented and passionate Natural Language Processing (NLP) Engineer with 2-5 years of experience to join our growing AI team.

The ideal candidate will be instrumental in designing, developing, and deploying robust NLP models and systems that power our core products and services.

You will work on challenging problems involving text analysis, information extraction, natural language understanding (NLU), and natural language generation (NLG), contributing directly to the intelligence of our applications.

Responsibilities :

Design, develop, and implement state-of-the-art NLP models and algorithms for various applications, including but not limited to :

- Text classification and categorization

- Named Entity Recognition (NER)

- Sentiment analysis

- Topic modeling

- Text summarization

- Question answering systems

- Chatbot development and conversational AI

- Preprocess, clean, and analyze large datasets of unstructured text data.

- Evaluate and fine-tune existing NLP models and frameworks (e.g., Transformers, BERT, GPT, SpaCy, NLTK).

- Collaborate with data scientists, machine learning engineers, and software developers to integrate NLP solutions into production systems.

- Conduct experiments and research to identify new opportunities for applying NLP techniques to business problems.

- Monitor and maintain the performance of deployed NLP models, ensuring scalability and reliability.

- Stay up-to-date with the latest advancements in NLP research and industry best practices.

- Document code, models, and experimental results clearly and concisely.

Qualifications :

Required Skills & Experience :

- Bachelor's or Master's degree in Computer Science, Linguistics, Artificial Intelligence, or a related quantitative field.

- 2-5 years of professional experience in Natural Language Processing.

- Strong programming proficiency in Python.

- Solid understanding of core NLP concepts, algorithms, and models.

Hands-on experience with popular NLP libraries and frameworks such as :

- Hugging Face Transformers

- PyTorch or TensorFlow

- SpaCy, NLTK, Gensim

- Experience with data preprocessing, feature engineering, and model evaluation techniques for text data.

- Familiarity with machine learning concepts and algorithms beyond NLP (e.g., supervised, unsupervised learning).

- Experience working with cloud platforms (AWS, GCP, Azure) for deploying ML models is a plus.

- Excellent problem-solving skills and the ability to work independently and as part of a team.

- Strong communication and presentation skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Skills :

- Experience with large language models (LLMs) and their applications.

- Familiarity with MLOps practices for deploying and managing NLP models in production.

- Knowledge of distributed computing frameworks (e.g., Spark) for large-scale data processing.

- Experience with containerization technologies (Docker, Kubernetes).

- Contributions to open-source NLP projects or relevant publications