Freelancer

Key Skills

Software

No software listed

Top Subject Matter

Hardware

electronics (EE): RTL/Verilog

digital design

processor architecture (RISC-V

SRAM

Top Data Types

Text

Audio

Computer Code Programming

Top Task Types

Bounding Box

Polygon

Point/Key Point

Polyline

Segmentation

Relationship

Freelancer Overview

Electrical Engineering student at IIT Delhi (graduating 2026) with a Columbia MS admit in AI and EE, and hands-on experience evaluating and improving AI systems. My edge is hardware: I worked on a remote internship at Harvard’s Edge Computing Lab on an RTL-generation LLM, where I built the prompting layer in LangChain, integrated a silicon compiler into the pipeline, and ran and tested model-generated RTL designs (RISC-V, SRAM, BlackParrot) to judge whether the Verilog output could actually replace existing modules. That work was equal parts prompt engineering, output evaluation, and technical correctness judgment. Beyond hardware, I have research-level machine learning experience, including computer vision pipelines for clinical sleep video analysis and work on probing LLM reasoning. I’m comfortable with the full stack of AI training tasks: LLM evaluation, code and RTL annotation, prompt-response quality, and reasoning correctness. My background is heavily quantitative (EE at IIT Delhi, top 0.2% in the national entrance exam), so I’m reliable on math, logic, and technical-domain labeling where most annotators aren’t. I’m precise, fast, and care about getting the details right. If you need someone who can label or evaluate technical data, especially in hardware, code, or ML, and explain their judgments clearly, I’m a strong fit.

Labeling Experience

Education

Work History