Related skills
pytorch llms rag langchain huggingface📋 Description
- Design and deploy AI solutions using RAG, embeddings, and vector databases.
- Build agent-based systems for document processing and knowledge retrieval.
- Implement MCP and multi-agent frameworks to orchestrate LLM workflows.
- Develop multi-modal GenAI experiences across text, images, and data.
- Evaluate and fine-tune foundation models for domain-specific impact.
- Collaborate with engineers, PMs, and stakeholders on production AI systems.
🎯 Requirements
- Advanced degree (MS/PhD) in CS, Data Science, AI, or related field.
- 5+ years in data science, ML, or applied AI with production deployments.
- Deep expertise in LLMs & GenAI, incl. RAG, embeddings, and vector search.
- Strong Python skills with Hugging Face, LangChain, LangGraph, PyTorch.
- Cloud-native expertise (Azure, AWS, Databricks) for GenAI services.
- Strong foundation in data science methods, stats, experiments.
- Strong analytical and problem-solving skills; optimize data workflows.
- Quick learner with passion for staying ahead of GenAI ecosystem.
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