Headline

Software Engineer @ Arista Networks | Ex-Nutanix MTS Intern | ICPC Regionalist’25 | B.Tech CSE, MNIT Jaipur ’26 | Agentic AI • GenAI • Deep Learning | Backend | C++ & Python | CF Expert • CC 4⭐ • LC Guardian

About

I'm a Software Engineer at Arista Networks, with a background spanning backend systems, applied AI/ML, and research. I recently graduated from MNIT Jaipur with a B.Tech in Computer Science (CGPA: 9.43/10). 📌 Professional Experience: • Most recently, I worked as an MTS Intern (AI/ML) at Nutanix, where I built and scaled RAG pipelines — improving retrieval accuracy from 67% to 85%, migrating components to an agentic LangGraph architecture, and designing API-throttling systems that improved reliability by 40% across user groups. • Before that, I was a Research Intern at Monash University, working on hate-to-non-hate speech conversion using ASR and LLM-based pipelines, and a Deep Learning Research Intern at MNIT, where I designed a novel attention-based architecture for multi-label ophthalmic disease classification, improving accuracy from 58.9% to 66.2% over state-of-the-art baselines. 📌 Key Projects: • AI-Powered E-Commerce Marketplace — Amazon HackOn'25 (Top 130/15k+ teams) • Arbitrage Trading Simulator — real-time NSE/BSE data processing with a parallelized C++ engine 📌 Competitive Programming: Codeforces Expert • CodeChef 4★ • LeetCode Guardian • ICPC Asia-West Regionalist'25 📌 Other Achievements: JEE Advanced Rank 6230 • JEE Mains Rank 5222 • NTSE Level-1 Scholar Always happy to connect.

Location

Bengaluru

AI stack

claude code

cursor

hugging face

langchain

langgraph

mcp

Work experience

Software Engineer at Arista Networks, Jul 2026 - Present · 2 mos, Bengaluru

Intern MTS at Nutanix, Aug 2025 - Dec 2025 · 5 mos, Bengaluru, Karnataka, India

NLP Research Intern at Monash University Malaysia, May 2025 - Jul 2025 · 3 mos, Remote, Utilized multiple Hugging Face ASR models including Wav2Vec2 (base & large), Distil-Whisper (large v3.5), Canary-1B Flash, and Parakeet-TDT (0.6B V2) on custom datasets, followed by evaluation using WER, BLEU, Semantic Similarity, and LENS metrics. Applied few-shot Chain-of-Thought prompting techniques on various LLMs, including GPT-4.1, Gemini-2.0, and Mixtral, with rigorous evaluation of model outputs using standardized metrics for language generation quality. Also explored additional model variants like DeepSeek during experimentation.

Deep Learning Research Intern at Malaviya National Institute of Technology Jaipur, Jan 2025 - Mar 2025 · 3 mos, Jaipur, Rajasthan, India, Developing an Intelligent Multi-Label Ophthalmic Disease Diagnostic Model using deep learning. Experimenting with Convolutional Neural Network (CNN) architectures, including GoogleNet, Inception v3, VGGNet, ResNet, DenseNet, EfficientNet, MobileNet, ConvNeXt, and Vision Transformers including ViT, MaxViT, MobileViT, and Convolutional Transformer. Exploring Graph Convolutional Networks (GCNs) to model disease correlations and improve classification performance. Implementing state-of-the-art architectures from top-tier Deep Learning, Computer Vision, and Medical Imaging Conferences, including ICLR, CVPR, ICCV, ECCV, MICCAI, and AAAI. Developing a novel deep learning model tailored for Multi-Label Ophthalmic Disease classification using fundus images.

Education

Bachelor's of Technology - B.Tech, Computer science and Engineering, Malaviya National Institute of Technology Jaipur

Public links

github: https://github.com/jatinjindal1203

leetcode: https://leetcode.com/jindal1203

codeforces: https://codeforces.com/profile/jindal1203