NLP Engineer

Skills:

Python, Natural Language Processing, Machine Learning, BERT, Large Language Models (LLM), Retrieval-Augmented Generation (RAG), Knowledge Graphs,

Job Overview

We are seeking a Junior NLP Engineer to join our team in Hyderabad on a full-time basis. The successful candidate will play a crucial role in enhancing our AI capabilities, particularly in developing and implementing natural language processing solutions. You will be working closely with other departments to improve user experience, streamline data processing, and elevate our technology stack to meet the evolving needs of our platform.

Qualifications And Skills

• Proficiency in Python programming language is essential for developing and deploying NLP models effectively.
• Strong understanding of Natural Language Processing principles and techniques to drive innovations in our AI offerings.
• Expertise in Machine Learning methodologies and algorithms to enhance data interpretation and processes.
• Experience with Knowledge Graphs to facilitate advanced data linking and improve information retrieval.
• Familiarity with BERT (Mandatory skill) for effective language representation and natural language understanding.
• Knowledge of Large Language Models (LLM) (Mandatory skill) to enhance the scale and capability of language tasks.
• Experience in Retrieval-Augmented Generation (RAG) (Mandatory skill) for state-of-the-art information retrieval.
• Ability to adapt quickly to emerging technologies and integrate them into existing systems.

• Design and implement NLP models to enhance the AI-driven features of our photography management platform.
• Collaborate with cross-functional teams to align NLP solutions with business objectives and user needs.
• Conduct research and stay updated with the latest advancements in NLP and AI to integrate best practices.
• Analyze and process large sets of data to improve the accuracy and efficiency of language models.
• Optimize NLP applications for performance and scalability, ensuring seamless integration with our systems.
• Develop and maintain documentation for NLP models and processes to streamline future iterations and updates.
• Identify opportunities for process improvements and make recommendations to technology teams.
• Ensure that all NLP solutions adhere to company standards and contribute to the overarching brand mission.