Model Development & Fine-tuning:

Build, fine-tune, and deploy advanced machine learning and natural language processing models (LLMs, GPT, Bard, Gemini) to solve complex business problems.

LLM & NLP Expertise:

Leverage cutting-edge NLP techniques to build and optimize solutions for tasks like text generation, summarization, sentiment analysis, question answering, and entity recognition.

Integration of LangChain & LLAMA Index:

Integrate LangChain, LLAMA Index, and other frameworks to build scalable and efficient AI systems that can interact with external data sources and APIs.

Vector Databases & RAG Systems:

Implement and manage vector databases (e.g., Pinecone, FAISS) for retrieval-augmented generation (RAG) systems, optimizing search and retrieval of relevant data to improve the accuracy and context of AI outputs.

API Development & Deployment:

Build and deploy machine learning models as scalable REST APIs using frameworks such as FastAPI, Flask, and Django to serve AI-driven solutions in production environments.

Cloud Infrastructure & Deployment:

Utilize cloud platforms (e.g., AWS SageMaker) for model training, deployment, and scaling. Ensure efficient model pipelines for continuous integration and deployment (CI/CD) of AI solutions.

AI Applications in Speech and Vision:

Work on advanced AI models such as Whisper AI (for speech-to-text) and Stable Diffusion (for image generation). Integrate these models into enterprise applications.

OCR Systems:

Develop and optimize Optical Character Recognition (OCR) solutions for document processing, text extraction, and analysis using deep learning models.

Collaboration & Innovation:

Collaborate with cross-functional teams, including data scientists, software engineers, and business stakeholders, to deliver AI solutions that create business impact.

Research & Development:

Stay updated with the latest advancements in AI, LLMs, NLP, and related technologies to keep the company ahead of industry trends.

Education:

Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Data Science, or a related field.

Strong experience with Large Language Models (LLMs)

, including GPT, Bard, and Gemini.

2-3 Years of Hands-on experience with LangChain

and LLAMA Index

for building robust LLM-driven applications.

Proficiency with NLP tools and techniques

, including named entity recognition (NER), sentiment analysis, text generation, and summarization.

Experience with Vector Databases

(e.g., FAISS, Pinecone) for similarity search and RAG systems.

Proficient in machine learning frameworks

(e.g., TensorFlow, PyTorch) and deep learning

(e.g., CNNs, RNNs, Transformers).

Strong skills in API development

using FastAPI

, Flask

, or Django

for building scalable solutions.

Experience with cloud platforms

(AWS, GCP, Azure) and using tools like AWS SageMaker

for deploying models at scale.

Familiarity with generative AI models like Stable Diffusion

(for image generation) and Whisper AI

(for speech recognition).

Knowledge of OCR

tools and frameworks (e.g., Tesseract, EasyOCR) for document and text extraction.