Data Scientist
Tasks
- Build and fine-tune language models
- Build and optimize vector database solutions
- Build machine learning pipelines
- Conduct exploratory data analysis and statistical analysis
- Design deep learning architectures for NLP and computer vision
- Develop and deploy machine learning models
- Develop metrics and studies for product value
- Develop prompt engineering and tuning
- Implement retrieval-augmented generation
- Mine and analyze customer data for product insights
- Perform data collection preprocessing and feature engineering
- Train NLP models for classification extraction and question answering
Perks/Benefits
- N/A
Skills/Tech-stack
Apache OpenNLP | Autogen | Azure OpenAI | BERT | Computer Vision | CoreNLP | Deep learning | Entity recognition | FastAPI | Flask | Generative AI | Gensim | Graph Databases | Keras | Knowledge graphs | Langchain | Language Models | Large Language Models | Llamaindex | LoRA | Machine Learning | NLP | NLTK | Named Entity Recognition | OpenAI GPT | PEFT | Pinecone | Postman | Prompt engineering | PyTorch | Python | QLoRA | Qdrant | Question Answering | R | Retrieval-Augmented Generation | Spacy | Swagger | TensorFlow | Text Classification | Text Summarization | Topic Modeling | Transformer | Vector Databases
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