Data Scientist
Tasks
- Apply statistical methods and feature engineering
- Build generative AI solutions with RAG and AI agents
- Collaborate with research engineering and business stakeholders
- Create reusable modeling pipelines and AI tools
- Deploy production-ready AI solutions
- Develop AI architectures for NLP computer vision and conversational AI
- Develop machine learning models for LLMs and NLP
- Implement vector database based retrieval systems
- Perform prompt engineering and model fine-tuning
- Preprocess analyze and transform data for insights
- Provide technical leadership and documentation
Perks/Benefits
Skills/Tech-stack
AWS | Autogen | Azure | BERT | Computer Vision | Conversational AI | CoreNLP | ELMo | FastAPI | Feature Engineering | Fine Tuning | Flask | GCP | Generative AI | Gensim | Keras | Langchain | Language Models | Language Processing | Large Language Models | Llamaindex | LoRA | Machine Learning | NLTK | Natural Language | Natural Language Processing | OpenNLP | PEFT | Postman | Prompt engineering | PyTorch | Python | Q LoRA | Question Answering | RAG | Spacy | Supervised Learning | Swagger | TensorFlow | Unsupervised Learning | Vector Databases | XLNet
Education
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