Principal AI/ML Engineer

- Define and lead the technical vision and roadmap for AI/ML and IDP capabilities across various products and programs. - Set architectural standards, design patterns, and best practices for scalable, secure, and maintainable AI systems. - Evaluate new technologies, research advancements, and tools in Generative AI, LLMs, OCR, and NLP, recommending adoption where fitting. - Act as the principal technical authority for AI/ML design decisions and solution trade-offs. - Design end-to-end Intelligent Document Processing solutions utilizing OCR, NLP, LLMs, and additional deep learning models. - Oversee the implementation of production-grade ML systems, encompassing data pipelines, model training workflows, evaluation frameworks, and inference services. - Lead the development of reusable AI/ML frameworks, services, and accelerators applicable across a range of projects. - Ensure all solutions adhere to performance, scalability, reliability, and security requirements. - Guide the application of LLMs and other generative models for document interpretation, information extraction, summarization, classification, and query response. - Establish best practices for prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and model evaluation. - Supervise experimentation and model benchmarking to enhance solution accuracy and efficiency continually. - Collaborate with data engineering teams to create robust data ingestion, labeling, and feature engineering pipelines. - Define and implement MLOps best practices, such as versioning, model governance, monitoring, and automated deployment. - Ensure adherence to responsible AI practices, including model transparency, bias reduction, and auditability wherever applicable. - Team up with product managers, customers, and business stakeholders to translate high-level needs into technical AI/ML solution designs. - Clearly communicate complex AI/ML concepts to non-technical audiences, including executives and clients. - Collaborate closely with engineering leaders to align AI/ML projects with overall platform architecture. - Mentor and support both senior and junior engineers, encouraging technical growth and engineering excellence. - Lead technical design reviews, code analyses, and architectural discussions. - Foster an atmosphere of innovation, knowledge sharing, and continuous learning within the engineering team.