Freelance AI Engineers in New Delhi
Freelance AI Engineers in New Delhi
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Wahid Ali
pro
Ghaziabad, India
Full Stack Developer | AI Tool, Web App, MVP & SaaS Products
$10k+
Earned
4x
Hired
4.9
Rating
20
Followers
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Full Stack Developer | AI Tool, Web App, MVP & SaaS Products
1
Innovation Intelligence Platform
1
7
1
AI Search Optimization Platform
1
9
1
Flight Booking Platform
1
6
1
Digital Business Card Platform
1
4
AI Engineer
(2)
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Satya Prakash
pro
New Delhi, India
Mobile App Architect • React Native Expert • 50+ App Shipped
5.0
Rating
9
Followers
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Mobile App Architect • React Native Expert • 50+ App Shipped
1
GymCare Management System Development
1
1
1
Stellar Baby Mobile Application
1
4
1
Rizz AI: Image Generation App Development
1
2
1
Voice-First Productivity App Development
1
2
AI Engineer
(5)
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Dishant | Ex - Instantly, Copilot, Loti
max
Gurugram, India
Full Stack Engineering | Framer Expert | Figma | AI/ML
$25k+
Earned
8x
Hired
5.0
Rating
79
Followers
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Full Stack Engineering | Framer Expert | Figma | AI/ML
0
Materiaz - AI Powered Materials Intelligence Platform
0
4
1
Custom Shopify E-commerce UX & Development
1
1
1
Fitness & Coaching Platform Design
1
12
1
Chateeze AI Chat Platform | Web Design & Development
1
5
AI Engineer
(1)
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Rishi Bajpai
Noida, India
Building MVPs for startup founders with clean UX in a week.
1x
Hired
5.0
Rating
56
Followers
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Building MVPs for startup founders with clean UX in a week.
0
Tenderseal - AI-Driven Tender Management Platform Development
0
0
2
Reqwest - Designing an Efficient API Testing Platform
2
2
1
SpongebobLabs - AI Research Lab Website Development
1
2
0
SaaSking AI - Enterprise Website Redesign
0
0
AI Engineer
(1)
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Trashu Vashisth
Delhi, India
Building Production-Grade AI Agents & RAG Systems
7
Followers
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Building Production-Grade AI Agents & RAG Systems
4
Built a highly scalable Retrieval-Augmented Generation (RAG) chatbot designed to interact with private datasets/PDFs. Unlike standard LLMs, this system minimizes hallucinations by retrieving real-time context from a local knowledge base before generating responses. Key Features: Semantic Search: Implemented Vector Embeddings to perform high-speed similarity searches across thousands of document chunks. Smart Retrieval: Integrated a retrieval pipeline using LangChain to fetch the most relevant context for user queries. Source Citation: Configured the bot to provide source references from documents, ensuring data transparency and accuracy. Optimized Performance: Used FAISS/Chromadb for efficient vector storage and retrieval.
4
184
1
Developed a full-stack RAG-based E- Commerce AI chatbot using React.js and Tailwind CSS that suggests the perfect laptop from a live catalog. Integrated ChromaDB with BGE Embedding models to provide highly accurate, context-aware product recommendations and instant technical support." Key Highlights: Smart Laptop Recommendations: Uses Semantic Search to match user needs (gaming, coding, etc.) with real-time specs. Advanced Tech Stack: Powered by LangChain for orchestration and BGE models for superior data retrieval. Modern UI/UX: Built a responsive, clean interface using React.js and Tailwind CSS. Zero Hallucination: Ensures all suggestions are strictly grounded in the available product inventory.
2
1
86
3
Developed a high-precision Resume Parser using a custom-trained RoBERTa model, specifically fine-tuned for Named Entity Recognition (NER) tasks. This tool automates the extraction of critical information from unstructured resumes with deep learning accuracy. Key Features: NER-Based Extraction: Accurately identifies entities like Name, Experience, Skills, Education, and Contact Info. RoBERTa Architecture: Leverages Transformer-based embeddings for superior contextual understanding compared to traditional parsers. JSON Output: Seamlessly converts complex resume layouts into structured JSON format for easy database integration and ATS (Applicant Tracking System) workflows. High Accuracy: Trained to handle diverse formatting and professional jargon.
3
151
4
Developed an automated pipeline to handle bulk recruitment workflows. This AI-powered tool processes multiple PDF resumes simultaneously, using advanced parsing to extract candidate details with high accuracy. It intelligently structures unstructured resume data into a clean, downloadable CSV format, capturing essential metrics like skills, experience, and contact info without manual data entry.
4
232
AI Engineer
(1)
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Jagwinder Singh
pro
Delhi, India
Full Stack Developer
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Full Stack Developer
0
AI Tattoo Generator App
0
0
0
Second Line App for Private Secondary Phone Numbers
0
0
0
Redesign for Improved Engagement
0
0
0
Development of a Scalable Food Delivery App
0
0
AI Engineer
(1)
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ANIMESH SINGH
Delhi, India
Data & AI Engineer
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Data & AI Engineer
3
Problem: Many organizations still process invoices manually by reading PDF documents and entering key details (invoice number, vendor, amount, etc.) into systems. This process is slow, error-prone, and difficult to scale, and it also makes it harder to detect duplicate invoices or incorrect totals. Solution: This project builds an automated invoice processing pipeline that converts uploaded invoice PDFs into structured data. It uses OCR to extract text, LLMs to identify invoice fields, validation checks to ensure correctness, and Kafka-based event streaming to manage the processing pipeline. The extracted data is stored in PostgreSQL and visualized through a dashboard, enabling faster, scalable, and more reliable invoice processing.
3
3
121
0
A fully local RAG pipeline that transforms your PDFs into a queryable knowledge base using FAISS vector search and Ollama LLMs. No cloud, no API keys - just private, grounded document intelligence running entirely on your machine.
0
28
0
Problem Statement Urban traffic management systems lack real-time, integrated data combining traffic conditions with weather patterns. This results in poor routing decisions, delayed emergency responses, and inefficient traffic flow management. Solution Developed a comprehensive real-time ETL pipeline that integrates traffic APIs and weather data sources, processes millions of data points, and delivers actionable insights through interactive dashboards for traffic management and route optimization.
0
25
0
A fully Dockerized real-time IoT ETL pipeline that simulates device telemetry, processes events through MQTT and Kafka, orchestrates workflows with Airflow, and delivers real-time alerts and insights to CRM systems with monitoring via Grafana and Loki.
0
45
AI Engineer
(2)
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Nitesh Agarwal
Delhi, India
I craft modern digital experiences with design-driven code.
New to Contra
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I craft modern digital experiences with design-driven code.
0
I developed a next-generation dental appointment platform featuring a real-time conversational AI assistant. "AIvory" helps patients discover dentists and manage their dental health using voice commands. Voice AI Integration: Integrated Vapi AI to create "Riley," a conversational assistant capable of answering dental queries and guiding users. Location Intelligence: Built a discovery engine using OpenStreetMap and Leaflet.js to find real dentists within a 10km radius. Smart Scheduling: Engineered a 3-step booking flow with automated calendar integration (.ics generation) and Resend API email confirmations. Secure Infrastructure: Implemented Clerk for multi-factor authentication and role-based access control (Admin vs. User). Tech Stack: Next.js 15, Vapi AI, Prisma, PostgreSQL (Neon), Tailwind CSS 4.
0
7
0
Project Title: Tastify - Spotify for Recipes Description: "What if finding dinner was as easy as finding a song?" I designed Tastify to answer that question. It is a modern recipe discovery platform that borrows the intuitive UX patterns of music streaming apps to make cooking accessible Familiar Interface: Adapted the horizontal scrolling and category browsing patterns users already love. Rich Media Integration: Integrated the YouTube API for seamless in-app video tutorials. Smart Search: Built a responsive search system that filters by ingredients and recipe names instantly. Micro-interactions: Focused on fluid transitions and animations to create a premium "native" feel. Tech Stack: React Native, Expo, TypeScript, Figma.
0
11
0
Project Title: Interactive 3D Web Experience Description: I built this interactive portfolio to challenge standard web navigation patterns. By combining the power of Next.js with the visual capabilities of Three.js, I created a "gamified" browsing experience that encourages exploration. WebGL Integration: Advanced manipulation of 3D scenes within a React context. Creative UI/UX: Implementation of non-linear navigation and thematic dark mode. Performance: High-speed page transitions and optimized asset delivery. Tech Stack: Three.js, Next.js, Framer Motion.
0
11
0
Modern Video Streaming Interface :- A comprehensive recreation of the Netflix web application, focusing on fluid user interactions and pixel-perfect design implementation. This project serves as a study in modern UI patterns and component composition Dynamic Portals: Created robust modal overlays for content details using React Portals to ensure proper stacking contexts. Cinematic Motion: Integrated Framer Motion to drive smooth, physics-based transitions for hover states and page navigation. Custom Video Engine: Developed a bespoke video player interface with custom controls and overlay logic using Video.js. Real-Time Data: Integrated the TMDB API to provide live search functionality and dynamic content categorization. Tech Stack: React, Material-UI, TMDB API, TypeScript.
0
9
AI Engineer
(1)
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