Browse categories
Explore
Fiverr Pro
English
$
USD
I will build nlp semantic search sentiment analysis and text ai
Senior AI Engineer, LLM RAG Computer Vision and ML Expert
I am a Senior AI Engineer with 3+ years of experience building production-ready AI, Machine Learning, Deep Learning, LLM, RAG, Agentic AI, NLP, Computer Vision, OCR, Data Engineering, and Power BI sol...
About this Gig
I will build NLP, Semantic Search, Text Analytics, Sentiment Analysis, and AI-powered search solutions for your text data.
I can process news articles, reviews, reports, documents, customer tickets, legal text, product descriptions, and enterprise knowledge bases. Services include semantic search with embeddings, LLM summarization, named entity recognition, sentiment analysis, text classification, topic modeling, keyword extraction, duplicate detection, re-ranking, and API integration.
Tech stack: Python, Hugging Face, Transformers, BERT, Sentence Transformers, OpenAI, Claude, ChromaDB, FAISS, Pinecone, Pandas, FastAPI.
Best for news platforms, media monitoring, customer feedback analytics, enterprise search, document intelligence, SaaS products, and research tools. Message me with your dataset and target output before ordering.
Programming language:
Python
•
SQL
•
NoSQL
•
MLflow
•
Amazon SageMaker
Frameworks:
Scikit-learn
•
Google ML Kit
•
Keras
•
PyTorch
•
Panda
My Portfolio
Other Data Science & ML Services I Offer
FAQ
Can you build a semantic search engine?
Yes. I can build semantic search using embeddings, vector databases, ranking, and re-ranking.
Can you summarize news or documents?
Yes. I can create LLM-based summarization pipelines for articles, documents, reports, and long text.
Can you extract names, locations, and organizations?
Yes. I can implement Named Entity Recognition and entity analytics.
Can you work with multilingual text?
Yes, depending on the language and available models. Please share language details before ordering.
Can you integrate this into my web app?
Yes. I can expose the NLP system as an API or integrate it into your backend.
