Job
Description
1. Overall 8+ years of experience with Python and data science toolkits (NumPy, Pandas, Scikit-learn). 2. Develop and deploy APIs and web applications using Flask. 3. Familiarity with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB). 4. Design, implement, and optimize advanced machine learning models, including supervised, unsupervised, and deep learning approaches. 5. Strong understanding of time series forecasting, Bayesian statistics, and optimization techniques. 6. Integrate different machine learning models into Flask applications for production use. 7. Ensure application security, scalability, and performance. 8. Experience with NLP frameworks and tools (e.g., NLTK, SpaCy Hugging Face). 9. Design and implement NLP systems for tasks such as text extraction, sentiment analysis, entity recognition, language modeling and conversational AI. 10. Build and fine-tune models using frameworks such as Tensor Flow, PyTorch, or Hugging Face. 11. Develop and optimize recommendation algorithms using collaborative filtering, content-based filtering, or hybrid approaches. 12. Analyze behavior and engagement metrics to improve recommendation accuracy. 13. Develop and fine-tune large language models (LLMs) using open-source frameworks such as Lang Chain, ensuring high performance and scalability. 14. Build Retrieval-Augmented Generation (RAG) applications independently using open-source LLM models. 15. Leverage cloud computing platforms (AWS, Azure, GCP, Data bricks) to deploy, monitor, and optimize models in production environments.
