Hi, I'm

Nisha Goswami

Engineer & Writer

Childhood memory
The Start

It started with a curiosity.

From curious childhood experiments to training complex ML models, my journey has been driven by an insatiable hunger to understand 'how'. I'm currently documenting my entire life path—failures, learnings, and small wins—in a detailed blog series.

Experience

06/2026 - Present

GTM Automation Engineer

VideoSDK

  • Building intelligent automations across GTM workflows — from lead ops to outreach and beyond!
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07/2025 - 10/2025

ML Intern

Reliance JIO Infocomm Limited

  • Applying my skills to real world problems & drinking some machine coffee!
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Projects

A small selection of projects that showcase my passion for building things!

HireFlowly - 1HireFlowly - 2
TypeScriptSupabaseVitestAI Semantic Matching

HireFlowly

HireFlowly is an intelligent, AI-powered resume analyzer designed to streamline the evaluation and optimization of professional CVs. By leveraging advanced natural language processing, the platform automatically parses uploaded resumes to extract key skills, experiences, and formatting details. It serves as a highly valuable tool for job seekers who want to improve their Applicant Tracking System (ATS) compatibility through targeted, data-driven feedback.

The Solution

Built a secure, full-stack AI pipeline using Supabase Edge Functions with strict CORS configuration to protect API keys and manage latency. Implemented precise prompt engineering to force the LLM to return strictly structured JSON outputs. Developed a comprehensive document parsing pipeline to handle complex PDF and DOCX files. Deployed on Vercel with systematic evaluation features to grade resume bullet points for authenticity and impact.

Drowsiness Detection System - 1
YOLOPyTorchComputer VisionReal-Time Detection

Drowsiness Detection System

A real-time computer vision system to detect driver drowsiness using YOLO and PyTorch.

The Solution

Developed a YOLO-based computer vision model in PyTorch to detect signs of driver drowsiness by monitoring facial landmarks such as eye closure and yawning frequency. The system processes live video feed from a camera and triggers an audible alert when drowsiness is detected.

Let's Collaborate Guys!

I'm always open to discussing new projects, creative ideas, or opportunities to be part of your visions.