Senior AI-ML Developer/ Gen-AI Engineer - AVP - C12 - PUNE

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 - 12 Years
• 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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