◦ Image Analysis and LLM Fine-Tuning: Working on solutions for performing image analysis using multi-modal LLMs and fine-tuning it for customer use-cases.

◦ MLOps Pipelines: Using different technologies to create full-scale MLOps pipelines on SageMaker for production deployment.

◦ WandB Reports: Creating high-quality Weights & Biases Reports around the newest trends in Computer Vision and Machine Learning

◦ Integrations: Developing new integrations for Weights & Biases with popular open-source libraries with logging capabilities

◦ Blog Posts: Writing highly technical and researched blog posts around different challenges within Computer Vision and Machine Learning

◦ Video Blogging: Developing informative videos around the written blog posts for generating educational content

◦ Research: Working towards a publication along Domain Adaptation problems in Autonomous Driving under Prof. C.V. Jawahar and Prof. Shankar Gangisetty

◦ Code Implementations: Operating with internal tools to perform large-scale GPU training and experimentation on Image Segmentation problems

◦ Demos and Examples: Work done towards adding newer demos, examples, and guides to the internal and external official documentation, most notably around converting torchvision models into TFLite

◦ Front-end and Back-end APIs: To work on adding to existing infrastructure for front-end and back-end functions in TensorFlow and JAX

◦ Internal AI Developer: To work on an AI Developer (Code-LLMs) that automates and builds upon the existing codebase and speeds up internal development, along with handling their training through Cloud resources like GCP and AWS

◦ Image Annotation Tool: In-house end-to-end tool, developed with TypeScript (APIs from/into Amazon RDS) and integrated into a React frontend to be used by doctors for tagging and annotation of patient images.

◦ ML CI/CD Pipeline: Designed and partially implemented a Continuous ML pipeline with use of AWS SageMaker, AWS RDS and AWS EC2 for deployment of a classifier.