Develop and implement novel NLP algorithms for text analysis and understanding, focusing on Indian languages.

Research and experiment with deep learning models like transformers for NLP tasks such as machine translation and sentiment analysis.

Curate and preprocess large datasets of text and speech data, ensuring quality and relevance for model training.

Evaluate and benchmark NLP models on standard datasets, identifying areas for improvement and optimization.

Collaborate with cross-functional teams to integrate NLP solutions into real-world applications and products.

Publish research findings in top-tier NLP conferences and journals, contributing to the advancement of the field.

Stay updated with the latest advancements in NLP and machine learning, attending workshops and reading research papers.

Develop and maintain NLP software libraries and tools, ensuring scalability and usability for other researchers.

Fine-tune pre-trained language models for specific tasks and domains, optimizing performance and resource utilization.

Conduct error analysis on NLP models, identifying common failure modes and developing strategies to mitigate them.

Design, build, and train NLP models using machine learning techniques.

Analyze large datasets to identify patterns and insights for model improvement.

Create and optimize algorithms for natural language processing tasks.

Conduct research to explore new NLP techniques and evaluate their effectiveness.

Write efficient and well-documented code for NLP applications.

Optimize model performance through hyperparameter tuning and architecture adjustments.

Stay updated with the latest research papers and advancements in NLP.

Work with cross-functional teams to integrate NLP solutions into products.

Create detailed documentation for models, code, and research findings.

Test and validate NLP models to ensure accuracy and reliability.

Deploy NLP models to production environments and monitor their performance.

Identify and fix bugs in NLP models and applications.