Freelancers using Google Gemini in DelhiFreelancers using Google Gemini in Delhi
"AI Brand Commercial Creator"
"AI Brand Commercial Creator"
Full Stack Developer
8
Followers
Full Stack Developer
Cover image for AI Resume Screening | Candidate
AI Resume Screening | Candidate Ranking System | AI HR Recruiter | ATS CV/Resume Optimization 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄 Recruiters often spend hours manually reviewing resumes, comparing candidate qualifications, and identifying the best fit for open positions. To address this challenge, I developed an AI-powered Resume Screening and Candidate Ranking Platform that automates candidate evaluation, improves hiring efficiency, and reduces recruitment time. 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲 Traditional recruitment processes involve reviewing hundreds of resumes for a single position. This manual approach is time-consuming, inconsistent, and often results in qualified candidates being overlooked. Recruiters needed a solution capable of quickly analyzing resumes, matching them against job requirements, and generating reliable candidate rankings. 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻 I built an intelligent recruitment platform that leverages Artificial Intelligence and Natural Language Processing (NLP) to automate resume analysis and candidate assessment. 𝗞𝗲𝘆 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: - ATS-compatible resume parsing for PDF and DOCX files - Automated extraction of skills, experience, education, certifications, and contact information - AI candidate matching based on job descriptions - Intelligent candidate scoring and ranking system - Semantic skill matching using NLP techniques - Automated shortlist generation for recruiters - Recruiter dashboard for managing applications and rankings - Bulk resume processing for high-volume recruitment - Interview recommendation system based on candidate fit - Fair and consistent evaluation framework to reduce manual bias 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 The platform was designed with scalability and accuracy in mind. The workflow begins by parsing uploaded resumes and extracting structured candidate data. AI models then compare candidate profiles against job requirements, analyzing technical skills, years of experience, educational background, and industry relevance. A ranking engine generates compatibility scores and presents candidates in order of suitability. Recruiters can review detailed scoring insights, compare applicants, and make faster hiring decisions. 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 The solution significantly improved recruitment efficiency and candidate discovery. 𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀 > Reduced manual resume screening time by up to 80% > Accelerated candidate shortlisting process > Improved recruiter productivity and hiring speed > Increased consistency in candidate evaluation > Enabled processing of hundreds of resumes within minutes > Enhanced talent identification through AI-driven matching 𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻 This AI recruitment platform transforms traditional hiring workflows by automating resume screening, ranking candidates intelligently, and helping recruiters identify top talent faster, more accurately, and at scale.
1
141
Websites & automations. AI-native workflow, design-led.
$5k+
Earned
18
Followers
Websites & automations. AI-native workflow, design-led.
Cover image for NanoMech: The Real-Time Multimodal AI
NanoMech: The Real-Time Multimodal AI Trading Assistant 📈🤖 Built for the Gemini Hackathon Traders know that in the market, seconds equal dollars. By the time you switch between your chart, your analysis tools, and your risk calculator, the candle has already moved, and your setup is gone. I wanted to fix this. For the Gemini Hackathon, I built NanoMech—an AI that sits on top of your screen, sees exactly what you see, and gives you a complete trade plan in seconds. No API keys required, and no leaving your chart. 💡 The Solution NanoMech runs as two frameless, transparent overlays on top of any trading platform. It uses Google Gemini 2.5 Flash's multimodal vision capabilities to visually read your screen and deliver instant insights. Overlay 1: Market Analysis Trend: Analyzes bullish/bearish market structure and moving average crossovers. Liquidity: Evaluates order book depth, bid/ask walls, and support/resistance zones. Momentum: Breaks down candlestick patterns, volume behavior, and price velocity. Overlay 2: Trade Setup & Risk Management AI-Extracted Targets: Instantly provides Entry Price, Target Price, and Stop Loss. Live CALC Engine: Calculates Risk Amount ($), Position Size (Units), and Risk-to-Reward (R:R) Ratio. Everything updates live as you type in your desired risk percentage. 🛠️ How It Works (Under the Hood) Vision-to-Text Processing: Captures the screen in real-time using the mss library and sends the raw screenshot to Google Gemini 2.5 Flash via the Google GenAI SDK. Prompt Engineering: Engineered strict structured prompts using [ANALYSIS] and [TRADE] tags to force the LLM to output reliably parseable price data. Regex Extraction: Uses regex to pull the exact Entry, Target, and Stop prices from the AI's response and wire them directly into the local risk calculator. Custom Desktop UI: Built always-on-top transparent overlays using Python's Tkinter, utilizing threading to keep the UI fully responsive during API calls. Hands-Free Scanning: Integrated a global hotkey (Ctrl+A+I) and an Auto Mode that scans the chart every 20 seconds. 🧗‍♂️ Challenges Overcome Structured LLM Outputs: Getting an LLM to consistently return prices in a parseable numeric format is notoriously tricky. We solved this with rigorous prompt engineering and robust fallback handling. Thread-Safe UI: Tkinter isn’t thread-safe. We engineered a solution to route all UI updates through root.after() callbacks from the active analysis thread. UX/UI Friction: Tuning the transparency and colors so the text remains readable across both dark and light chart themes, while ensuring our global hotkeys didn't conflict with native trading platforms. 🚀 What We Learned & What's Next This project proved just how incredibly capable Gemini 2.5 Flash is at visual reasoning. It accurately identified complex candlestick patterns, moving averages, and volume spikes from a raw image alone. The Roadmap for NanoMech: Voice Output: Speaking the trade setup aloud for a 100% hands-free experience. Multi-Monitor Support: Allowing users to select which screen the AI tracks. Cloud Hosting: Running NanoMech as a scalable web service on Google Cloud Run. Trade Logging: Automatically tracking how the AI's setups perform over time. 💻 Built With Python | Google Gemini 2.5 Flash | Google GenAI SDK | Google Cloud | Tkinter | mss | pillow | Regex Ready to try it out? Check out the code and run it yourself: https://github.com/omshukla24/NanoMech
0
118
Web developer building responsive and modern websites
34
Followers
Web developer building responsive and modern websites