End-to-end model development with TensorFlow/PyTorch for computer vision (facial recognition, emotion detection), LLM fine-tuning, multimodal AI systems, on-device inference (TFLite/Core ML), and document intelligence using LLMs + OCR for summarization and data extraction.
Full‑stack web and mobile application engineering with React/Next.js, Flutter, Node.js/Express, Python/FastAPI/Django/Flask, and TypeScript—clean architectures, automated testing (Jest/PyTest), performance tuning, and accessibility best practices.
Design and operate REST/GraphQL services, event-driven pipelines, model serving (FastAPI/TorchServe), MLOps with MLflow/Apache Airflow, feature stores, CI/CD for ML, monitoring/observability, and secure auth/analytics for production AI systems.
AWS-first delivery: Serverless (Lambda, API Gateway, S3, DynamoDB, SageMaker, Bedrock), containers (Docker, ECS/EKS), IaC (CloudFormation/Terraform), CI/CD, Kubernetes, Azure AI services, and comprehensive monitoring for scalable, reliable AI systems.
AI/ML-focused software engineer specializing in designing and deploying intelligent systems (LLMs, semantic search, vector databases) with cloud-native MLOps. Proven ability to build scalable, privacy-preserving solutions for web, mobile, and enterprise applications.