AI Innovation Lead

4 days ago

ballari, India beBeeArtificialintelligenceengineer Full time

About the Role:We are seeking an experienced AI Engineer to lead the development and optimization of our software products' core AI features and IT projects.This role requires deep expertise in Large Language Models (LLMs), RAG systems, and Computer Vision for document and media intelligence.The ideal candidate will be a hands-on builder with a strong strategic mindset to make critical decisions on model selection and training methodology.Key Responsibilities:Lead the end-to-end design, implementation, and optimization of Retrieval Augmented Generation pipelines to deliver accurate and contextual answers.Integrate, manage, and fine-tune commercial and open-source LLMs for use in chat interfaces and AI-powered applications.Optimize embedding strategies and manage vector databases to ensure high performance and low latency similarity search.Develop and enhance Optical Character Recognition (OCR) and document layout analysis solutions to process complex file types for RAG and embeddings.Implement Computer Vision models to process and extract intelligence from image and video files.Evaluate and make strategic decisions on when to use pre-trained models, fine-tune existing models, or build custom models from scratch to meet client requirements.Lead custom training and fine-tuning of machine learning models and pre-trained models for specific tasks.Establish machine learning operations best practices for CI/CD, monitoring, and scalable deployment of all AI components on major cloud platforms.Required Qualifications:Experience: 8+ years in AI/ML Engineering, with at least 4+ years focused on Generative AI and production-grade LLM applications.Expert proficiency in Python and machine learning frameworks.Deep hands-on experience with LLMs, RAG architectures, prompt engineering, and vector databases.Strong background in Computer Vision, OCR, and document intelligence.Familiarity with orchestration frameworks.Solid understanding of software engineering best practices, API design, and microservices architecture.Bachelor's or Master's degree in Computer Science, Data Science, or a related field.Experience with Cloud machine learning operations tools and containerization (Docker, Kubernetes).

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