mohith
Mohith
LLM inference & evaluation

Hey, I’m Mohith.

I measure and build the systems that serve LLMs.

Final-year CS student and independent researcher.

Two preprints on LLM inference and eval reliability, GSoC '26 contributor at RUXAILAB , and former product developer intern at Koncepts. Currently building ServeBench, an environment for evaluating agents on LLM serving.

Experience

A few places I’ve built, learned, and taken responsibility.

THE FOUNDATION

Chinmaya Vishwavidyapeeth

B.Tech, Computer Science

Sep 2023 to May 2027CGPA 9.85 / 10.0

Recognition

  • Selected as 1 of 6 presentersIndia Builds with Claude (Anthropic × Razorpay), from 2,300+ applicants
  • 1st placeOpenAI Codex Community Hackathon, Calicut (for kea)
  • Dean's Merit Listranked 1st in CS department
  • Mintlify Open Source ProgramAntiVibe

Work

04 PROJECTS

AI infrastructure, developer tools, and a few things I wished existed.

Latest writing

All posts →
8 min read

Reward Hacking: When the Model Learns the Metric Instead of the Task

Notes on reward hacking in reinforcement learning and RLHF: what it is, why RL is so prone to it, Goodhart's Law and its four flavors, how it shows up in LLMs (sycophancy, evaluator hacking, in-context reward hacking), and the mitigations that exist today.

Reinforcement LearningRLHFAI SafetyReward HackingLLMs

Activity

0
Contributions
0
Merged PRs
0
Stars earned
0
Public repos

Stack

Every day

What I open without thinking about it

vLLMPyTorchHugging FacePythonTypeScriptFastAPINext.jsPostgreSQLDockerGitClaude Code

Often

Reached for whenever the problem calls for it

llama.cppModalGGUF quantizationReactKubernetesRedisTailwindSupabaseVuePrometheusVercel

When it fits

Used in anger at least once, happy to again

JavaLangChainOllamaFirebaseMySQL

Learning

  • LLM serving & KV caches
  • RL environments
  • Post-training
  • GPU kernels (Triton)
A line that stays with me