LLM Applied Data Scientist (RAG/ NLP)
Tasks
- Analyze user generated content using NLP and multimodal methods
- Apply reinforcement learning for LLMs
- Build data processing and retrieval pipelines
- Create evaluation methodologies for models
- Develop agents and multi agent systems
- Develop embedding reranking and context engineering
- Enable models to use external tools apis and code interpreters
- Implement query rewriting
- Integrate RAG pipelines into production systems
- Optimize retrieval ranking pipelines
- Research advanced AI retrieval algorithms
- Train and fine-tune large language models
Perks/Benefits
Skills/Tech-stack
A Star | C plus plus | Computer Vision | Context engineering | Deep learning | Embeddings | Fine Tuning | GraphRAG | Indexing | Information Retrieval | Language Models | Language Processing | Large Language Models | MCTS | Machine Learning | Multimodal Learning | Mutiagent Systems | Natural Language | Natural Language Processing | PyTorch | Python | Query Understanding | RAG | Reinforcement Learning | Reranking | Retrieval-Augmented Generation | Supervised Fine Tuning | Vector Databases | Vector Search
Education
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