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Seek AI knowledge not just to advance your career, but to expand your possibilities and create the future you envision.
Amazon (July 2020 - Present)
Applied Scientist 2, Bangalore (July 2022 - Present)
Developing enterprise GenAI systems with transformer architectures and multi-agent LLM frameworks. Implementing multi-modal AI combining computer vision and NLP with PyTorch, and AWS Bedrock. Specializing in hybrid extraction-generation architectures for e-commerce applications.
Applied Scientist 1, Bangalore (July 2020 - June 2022)
Designed production ML systems using transformer-based architectures for NER. Implemented CV algorithms for catalog optimization and developed multi-question machine reading comprehension models for e-commerce applications.
Applied Scientist Intern, Bangalore (May 2019 - June 2019)
Improved NER models using BiLSTM with Attention networks, achieving significant reduction in training data noise. Worked on ML pipelines for text processing applications.
Full Stack Developer Intern, Jaipur
Built responsive web and mobile applications with MEAN stack and Ionic Cordova. Developed cross-platform solutions with optimized front-end features for educational applications.
PARSE: LLM Driven Schema Optimization for Reliable Entity Extraction
EMNLP 2025 | Anubhav Shrimal, Aryan Jain, et al.A novel LLM driven framework that autonomously refines JSON schemas and combines reflection based guardrails to significantly improve the accuracy, reliability, and robustness of structured entity extraction from unstructured text.
MARCO: Multi-Agent Real-time Chat Orchestration
EMNLP 2024 | Anubhav Shrimal, Stanley Kanagaraj, Kriti Biswas, et al.A framework for orchestrating multiple specialized LLM agents in real-time conversational systems, with robust guardrails for error recovery and complex task execution.
NER-MQMRC: Formulating Named Entity Recognition as Multi Question Machine Reading Comprehension
NAACL 2022 | Anubhav Shrimal, Avi Jain, Kartik Mehta, Promod YenigallaA novel approach reformulating NER as a multi-question machine reading comprehension task, achieving significant improvements in accuracy while reducing model proliferation and training costs.
Discovering Emotion and Reasoning its Flip in Multi-Party Conversations using Masked Memory Network and Transformer
A novel approach for emotion detection and reasoning in multi-party conversations, introducing the Emotion-Flip Reasoning task to identify triggers for emotional state changes.
Attention Beam: An Image Captioning Approach
AAAI 2021 | Anubhav Shrimal, Tanmoy ChakrabortyAdditionally, Published 3 research papers in Amazon internal conferences, including the Amazon ML Conference (AMLC) and the Amazon Computer Vision Conference (ACVC).
Also, received a US patent in 2025 on a System for Multiple Named Entity Recognition.
M.Tech. in CSE (July 2018 - May 2020)
CGPA: 9.23 (Silver medalist)
B.Tech. in CSE (Aug 2014 - June 2018)
Nanodegree
Attained Scholarships by Facebook for Deep Reinforcement Learning & Deep Learning Nanodegrees
Making AI make sense — I break down complex research, tools, and trends so anyone from beginner to expert can apply the latest in artificial intelligence.
Here is a glimpse of the kind of content I publish on my Channel
PyTorch, TensorFlow, Scikit‑learn, Deep Learning, NLP, Computer Vision
The projects I did in Machine Learning with PyTorch, Fastai, keras, Tensorflow, Scikit-learn.
GithubImplementation of RL algorithms (DQN, DDQN, Dueling-DQN, DDPG, MADDPG) in PyTorch
GithubI implemented 85+ popular data structures and algorithms questions in Python 3 & C++
GithubI send thoughtful, non-spammy updates whenever I publish new content about my life, stories, pictures and reflections on artificial intelligence and more.
I am usually booked out for 2-4 weeks in advance. So please provide me with that flexibility.
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