8 Draup Jobs

Responsibilities :

- Model Development and Optimization : Design, build, and deploy NLP models, including transformer models (e.g., BERT, GPT, T5) and other SOTA architectures, as well as traditional machine learning algorithms (e.g., SVMs, Logistic Regression) for specific applications.

- Data Processing and Feature Engineering : Develop robust pipelines for text preprocessing, feature extraction, and data augmentation for structured and unstructured data.

- Model Fine-Tuning and Transfer Learning : Fine-tune large language models for specific applications, leveraging transfer learning techniques, domain adaptation, and a mix of deep learning and traditional ML models.

- Performance Optimization : Optimize model performance for scalability and latency, applying techniques such as quantization, ONNX formats etc.

- Research and Innovation : Stay updated with the latest research in NLP, Deep Learning, and Generative AI, applying innovative solutions and techniques (e.g., RAG applications, Prompt engineering, Self-supervised learning).

- Stakeholder Communication : Collaborate with stakeholders to gather requirements, conduct due diligence, and communicate project updates effectively, ensuring alignment between technical solutions and business goals.

- Evaluation and Testing : Establish metrics, benchmarks, and methodologies for model evaluation, including cross-validation, and error analysis, ensuring models meet accuracy, fairness, and reliability standards.

- Deployment and Monitoring : Oversee the deployment of NLP models in production, ensuring seamless integration, model monitoring, and retraining processes.