Amardeep Kumar
I love maths, coding, and Machine Learning. I work at the intersection of AI research and engineering — tackling reasoning, alignment, and hallucination in LLMs across visual question-answering, spatio-temporal reasoning, code-switching, and multi-modality.
Currently a Software Engineer at DoorDash. Recently graduated from NYU Courant (MS CS, AI specialization). Previously built ML infrastructure at Instabase and Walmart, interned at PineGap.ai, and participated in Google Summer of Code. Published at EMNLP, ACL, and CIKM.
One day I want to start a profitable and calm business solving niche AI research problems.
Featured
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GenZ to AI Enz: A Roadmap for CS Grads Breaking into AI
A complete series taking CS students and early-career engineers from zero ML knowledge to building real AI systems with LLMs and agents.
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How We Cut ML Inference Latency by 40% on Kubernetes
The architecture behind our async model serving platform at Instabase — async workers, RabbitMQ, multi-level caching, and sticky routing to cut inference time by 40%.
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GupShup: Summarizing Code-Switched Conversations
Our EMNLP 2021 paper on abstractive summarization of Hindi-English code-switched conversations — introducing the GupShup dataset.
Recent Posts
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GenZ to AI Enz: Series Index
Full table of contents for the GenZ to AI Enz series - every post and walkthrough in order.
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Activation Functions: Why ReLU, GELU, and SiLU Exist
Why stacking linear layers isn't enough, and how activation functions like ReLU, GELU, and SiLU give neural networks their power.
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What is a Neural Network?
A neural network explained from scratch - neurons, weights, layers, and the forward pass - no ML background required.
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Fine-tuning Phi-2 with DPO on the Anthropic HH Dataset
Fine-tuning Microsoft's Phi-2 using Direct Preference Optimization (DPO) on the Anthropic Helpful and Harmless dataset with LoRA and 8-bit quantization.