---
title: "SHOBHIT RAJ - LLM Post Training - Intern in Bhubaneshwar | Tal"
description: "Meet SHOBHIT RAJ, B.Tech Undergrad at KIIT’26 | LLM Post Training - Intern @ Ethara AI based in Bhubaneshwar. AI stack includes gemini, hugging face, and langchain."
image: "https://tal.club/meet/shobhit-1/share-image"
---

# SHOBHIT RAJ on Tal

## Headline

B\.Tech Undergrad at KIIT’26 \| LLM Post Training \- Intern @ Ethara AI

## About

Most CS students build projects\. I build and ship them — deployed, documented, and open\-source\. I'm an AI Engineer and full‑stack developer who cares about real users, real traffic, and real constraints\. Over the past 2\+ years, I've built systems that range from Android apps running on\-device ML to backend services handling hundreds of concurrent requests\. Some highlights that separate me from typical "course \+ toy project" profiles: \- Built a multi\-threaded C\+\+ Deep Packet Inspection \(DPI\) engine with load balancing and fast\-path architecture, parsing real network traffic and classifying applications at scale\. \- Shipped a production\-ready digital watermarking web app \(Flask \+ Docker\) using DWT, SVD, and meta\-heuristic optimization, complete with live demo, metrics \(PSNR, SSIM, MSE, NCC\), and user\-friendly UI\. \- Designed and deployed REST APIs \(Node\.js, Express, MongoDB/PostgreSQL\) that serve 200\+ concurrent requests with sub\-100ms response times using indexing, caching, and robust error handling\. On the ML side, I combine strong fundamentals with hands\-on work: \- Selected for Amazon ML Summer School 2025 \(top \~5%\), with 80\+ hours of supervised/unsupervised learning, deep neural networks, LLMs, reinforcement learning, and causal inference\. \- Implemented end\-to\-end ML workflows: data prep, model training, evaluation, and serving, including experiments with generative AI and LLM\-based tooling\. Tech stack: Python, PyTorch, TensorFlow, Flask, Node\.js, Express, Docker, AWS, Firebase, Kotlin/Android, PostgreSQL, MongoDB, CI/CD, REST APIs, multithreading, networking\. I'm currently looking for AI Engineer / ML Engineer / Software Engineer roles where I can own features end\-to\-end: from idea, to model, to API, to production deployment\. If you're building systems at the intersection of AI and high\-performance backend engineering, I'd love to connect\.

## Location

Bhubaneshwar

## AI stack

gemini

hugging face

langchain

openai

## Work experience

LLM Post Training \- Intern at Ethara AI, Apr 2026 \- May 2026 · 2 mos, Remote, At Ethara AI, I focused on enhancing the performance of Large Language Models through post\-training workflows\. My role involved evaluating model responses to detect inconsistencies and hallucinations, which was crucial for improving output quality\. I designed various prompt strategies and validation techniques to ensure the reliability of the models, contributing to a more accurate response generation process\.

Training Specialist at Ethara AI, Apr 2026 \- May 2026 · 2 mos, • Evaluated AI\-generated outputs using structured analytical workflows\. • Identified logical inconsistencies, formatting issues, and edge cases in AI responses\. • Worked in fast\-paced environments requiring analytical thinking, workflow accuracy, and attention to detail\. • Collaborated within process\-driven systems for response validation and quality evaluation\.

Apprentice at Amazon ML Summer School, Aug 2025 \- Nov 2025 · 4 mos, Virtual, • Selected among the top 5% of applicants nationwide for Amazon's most competitive ML training program, outperforming thousands of CS students across India • Completed 80\+ hours of intensive training directly led by Amazon Scientists, covering LLMs, deep neural networks, reinforcement learning, causal inference, and sequential learning for time\-series prediction • Scored in the top tier of program assessments across 8 modules, demonstrating applied understanding of how ML systems operate at Amazon's scale in e\-commerce and cloud infrastructure • Built foundational expertise in generative AI and model fine\-tuning techniques, with direct exposure to real\-world deployment considerations from practicing Amazon researchers • Engaged in live technical Q&As with senior Amazon ML Scientists, bridging theory with production\-grade applications in recommendation systems and demand forecasting

Keploy API Fellowship – Master of APIs at Keploy 🐰, May 2025 \- Jul 2025 · 3 mos, Virtual, • Architected and deployed 5\+ production\-ready REST APIs using Node\.js, Express\.js, and MongoDB, each with comprehensive input validation, error handling, and Swagger/OpenAPI documentation • Cut API regression bugs by 40% through systematic test automation using Keploy CLI — generating, replaying, and maintaining test suites across the full development lifecycle • Built RESTful services handling 200\+ concurrent requests with sub\-100ms response times, achieved through efficient database indexing and query optimization strategies • Delivered all 12 assignments ahead of schedule with zero revision requests, maintaining the highest completion rate in a cohort of 20\+ fellows across India • Contributed 3 merged pull requests to Keploy's open\-source codebase, improving CLI documentation clarity and increasing test case reliability for downstream users • Led weekly peer code reviews and pair programming sessions, identifying recurring API design anti\-patterns and sharing fixes across the cohort

## Education

Bachelor of Technology, Computer Science, KIIT \- Kalinga Institute of Industrial Technology

12th, PCM, Sri Chaitanya College of Education

[View the original profile](https://tal.club/meet/shobhit-1)

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