Suvaditya Mukherjee

Suvaditya Mukherjee

ML Intern @ Harman | Google Developer Expert (Machine Learning) | External Author @ PyImageSearch | Author @ Weights & Biases

NMIMS University

Harman International


He is a ML Intern at Harman International, a Google Developer Expert for Machine Learning, an External Author for PyImageSearch, an Author for Weights & Biases, and a student of the Bachelors in Artificial Intelligence Program at NMIMS MPSTME, Mumbai.

  • Machine Learning
  • Computer Vision
  • Deep Learning
  • Natural Language Processing
  • Generative Modelling
  • B.Tech in Artificial Intelligence, 2024

    NMIMS University


Harman International
ML Intern
December 2023 – Present Remote, Bengaluru, India

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.

Weights & Biases
October 2023 – Present Remote, San Francisco (CA), United States of America

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

External Author
June 2023 – Present Remote, New York City (NY), United States of America

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

Center for Visual Information Technology, IIIT-Hyderabad
Research Intern
June 2023 – October 2023 Hyderabad, Telangana, India

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

Ivy (
ML Research Engineer Intern
January 2023 – July 2023 Remote, London, United Kingdom

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

Mosaic Wellness
Software Engineer Intern
May 2022 – July 2022 Mumbai, Maharashtra, India

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.


A simple application developed in Flutter that enables transcribing information from images using Google MLKit For Flutter
Temporal Latent Bottleneck - TensorFlow
This is an unofficial implementation of the paper “Temporal Latent Bottleneck - Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning” by Didolkar et. al., developed jointly by Aritra Roy Gosthipaty and Suvaditya Mukherjee
Temporal Latent Bottleneck - TensorFlow

Recent & Upcoming Talks


Reach out to me! I enjoy having conversations around Machine Learning, Computer Vision, Production Systems, and Google Cloud