Model Development: Assist in training, fine-tuning, and evaluating large language models (LLMs) for specific applications.
Data Preparation: Support data collection, preprocessing, and augmentation efforts to ensure high-quality input for model training.
Research Support: Conduct literature reviews and contribute to the exploration of new methodologies and tools in natural language processing (NLP), computer vision (CV), recommender systems and machine learning (ML).
Collaboration: Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to implement LLM solutions.
Documentation: Maintain clear and comprehensive documentation of model architectures, experiments, and results.
Testing & Evaluation: Participate in the testing and evaluation of model performance, providing insights and recommendations for improvements.
Continuous Learning: Stay updated on the latest trends and advancements in NLP and ML, actively seeking opportunities for professional development, and reading state of the art model research papers and implementing.
Desired Candidate Profile
Experience with cloud platforms (e.g., AWS, Google Cloud etc) for deploying machine learning models.
Understanding of transformer architectures and state-of-the-art LLMs.
Knowledge of best practices for data ethics and bias mitigation in AI.
Proficient in Python, PyTorch/TensorFlow.
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