:rocket: AI Engineer / Data Scientist (LLMs, RAG, NLP, AWS, K8s) We are looking for an experienced AI Engineer / Data Scientist to join our team and work on a production-grade AI pipeline that processes complex medical cases. This is not a research-only role — we need someone who can work on real-world, scalable AI systems deployed across cloud and on-prem environments. :mag_right: Project Overview You will work on an existing AI pipeline that: Ingests large and complex medical case files (multiple PDFs, sometimes hundreds of pages) Converts and extracts structured information from these documents Performs entity extraction and layout analysis Transforms unstructured medical data into structured, machine-readable formats Supports deployment across AWS, Azure, and on-premise environments Operates via Kubernetes-based worker services with SQS queues The system is already running — your job is to optimize, enhance, and extend it. :brain: Required Skills AI / ML Expertise • LLM fine-tuning (open-source or API-based models) • Prompt engineering (advanced, production-grade) • RAG (Retrieval-Augmented Generation) pipelines • NLP and document intelligence • Deep learning model fine-tuning: CNNs RNNs Preferably using PyTorch Engineering Skills Strong Python expertise Experience building scalable AI services Docker (containerization) Kubernetes (deployment & orchestration) Worker-based distributed systems Message queues (SQS preferred) Cloud & Infrastructure AWS (SQS, EKS, storage, compute) Azure (for some client deployments) Experience with on-premise deployment Ability to build solutions that can run offline :hospital: Domain (Bonus but Valuable) • Experience with medical documents or healthcare NLP • Knowledge of document layout analysis • Experience with tools like: LayoutLM OCR pipelines Document AI systems :dart: What We’re Looking For Someone who understands both AI modeling and production systems Able to optimize performance and scalability Comfortable working with large PDFs and complex document structures Experience with structured data extraction from unstructured content Can work independently and take ownership :package: Engagement Details Long-term opportunity Ongoing improvements and new client deployments Work across cloud and on-prem environments Competitive compensation based on experience If you’ve built real-world AI pipelines (not just notebooks) and enjoy solving complex document intelligence problems, we’d love to hear from you. Please include: Examples of similar systems you’ve built Experience with LLM fine-tuning and RAG Cloud & Kubernetes experience Availability and time zone [10:34 AM]Please share URL of job post with us and we will apply and send you screenshots Sorry for the hassle