Job Summary:
We are seeking a highly skilled AI/ML Data Scientist with 5-8 years of experience to design and implement cutting-edge AI solutions. The ideal candidate will have strong expertise in developing LLM-based chatbots, Retrieval-Augmented Generation (RAG), text-to-SQL applications, and document processing workflows. Familiarity with state-of-the-art models such as GPT-4, Gemini, and open-source LLMs is essential.
Responsibilities:
Experience Level:8 - 12Years
AI/ML Model Development:
Design, fine-tune, and deploy LLMs (e.g., GPT-4, Gemini, and open-source models) for chatbot and NLP applications.
Implement Retrieval-Augmented Generation (RAG) for efficient information retrieval from large datasets.
Data Processing & Text-to-SQL:
Build text-to-SQL pipelines to enable natural language queries for structured databases.
Process structured and unstructured data for applications such as classification, extraction, and summarization.
Document Processing:
Automate document workflows, including ingestion, classification, and data extraction, using advanced AI techniques.
Python Development:
Write scalable and efficient Python code for data pipelines, ML models, and integration with production systems.
Model Deployment:
Deploy and monitor AI/ML models using MLOps best practices.
Optimize and refine deployed models based on feedback and performance metrics.
Collaboration:
Work closely with cross-functional teams, including data engineers and developers, to deliver business-aligned AI solutions.
Qualifications:
Strong proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
5-8 years of hands-on experience in AI/ML, NLP, RAG, chatbot development, and LLM applications.
Expertise in working with LLMs and write Prompts to build LLM based applications (e.g., GPT-4, Gemini, Mixtral etc).
Hands-on experience with Retrieval-Augmented Generation (RAG) and vector databases.
Advanced skills in NLP techniques, text-to-SQL solutions, and document processing workflows.
Familiarity with cloud platforms (AWS, GCP, Azure) and containerization tools (Openshift, Kubernetes).
Knowledge of MLOps frameworks for model deployment and lifecycle management.
Education:
Bachelor's degree/University degree or equivalent experience
Bachelor's or Master's in Computer Science, Data Science, AI, or a related field.
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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Job Family Group:
Technology------------------------------------------------------
Job Family:
Applications Development------------------------------------------------------
Time Type:
Full time------------------------------------------------------
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