Freelance ML Engineers in PunjabFreelance ML Engineers in Punjab
ProjectsPeople
Arslan Mehmood's avatar
Arslan Mehmood
Lahore, Pakistan
ML AI | Backend | Computer Vision | GenAI | LLM Agents
New to Contra
ML AI | Backend | Computer Vision | GenAI | LLM Agents
Cover image for LakeShield - AI-Powered Video Monitoring
LakeShield - AI-Powered Video Monitoring and Vessel Intelligence Platform I led the development of LakeShield as the Senior AI/ML Engineer and Lead Developer, taking the platform from initial research and experimentation to a scalable production system. My responsibilities included: 🔹 Designing the end-to-end AI and video-processing architecture 🔹 Building YOLO-based boat and vehicle detection pipelines 🔹 Developing object tracking and movement-analysis workflows 🔹 Implementing OCR for extracting boat registration information 🔹 Creating scalable pipelines for processing thousands of surveillance videos 🔹 Developing FastAPI backend services and automated data workflows 🔹 Building a Next.js analytics dashboard integrated with Supabase 🔹 Deploying and operating the AI pipeline on cloud GPU infrastructure 🔹 Optimizing model accuracy, inference speed, infrastructure costs, and reliability 🔹 Managing production monitoring, troubleshooting, maintenance, and continuous improvements The platform transforms raw surveillance footage into structured operational insights, enabling automated vessel monitoring, vehicle activity analysis, registration extraction, and reporting. This project involved complete technical ownership across Computer Vision, AI/ML, backend development, cloud infrastructure, data engineering, MLOps, and production operations. #ComputerVision #VideoAnalytics #ArtificialIntelligence #ObjectDetection #OCR #MLOps #FastAPI #NextJS #Supabase #CloudEngineering
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Cover image for Shelfr - AI-Powered Retail Shelf
Shelfr - AI-Powered Retail Shelf Intelligence Platform I led the development of Shelfr as the Senior Computer Vision Engineer and Lead Developer, taking the platform from the initial idea and system architecture through development, deployment, and production operations. My work included: 🔹 Designing the complete computer vision and backend architecture 🔹 Building product detection, shelf analysis, OCR, and image-processing pipelines 🔹 Developing APIs and scalable data-processing workflows 🔹 Deploying and managing production systems on GCP cloud servers 🔹 Optimizing model accuracy, processing speed, and infrastructure performance 🔹 Managing production monitoring, reliability, troubleshooting, and ongoing improvements 🔹 Leading technical decisions across AI, backend, cloud infrastructure, and DevOps The platform converts real-world retail shelf images into structured product and shelf-level insights, helping automate retail auditing, product visibility analysis, and inventory workflows. #ComputerVision #RetailAI #LeadDeveloper #AIEngineering #GCP #MLOps #Python #CloudEngineering
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Cover image for ⚖️ Built a French Legal
⚖️ Built a French Legal AI Assistant powered by advanced RAG and LLM technology. The system enables users to ask complex legal questions and receive accurate, context-aware answers grounded in French legal documents. Key features include: 🔹 Custom legal document ingestion and chunking 🔹 Metadata-based vector search 🔹 Hybrid retrieval and reranking 🔹 Agentic RAG workflows using LangGraph 🔹 Source-grounded answers with legal references 🔹 Private deployment on an Azure VM using locally hosted LLMs The main focus was improving retrieval accuracy, reducing hallucinations, and making large collections of legal documents easier to search and understand. #LegalAI #RAG #LLM #ArtificialIntelligence #LangGraph #Azure #GenerativeAI #MachineLearning
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Cover image for AI-Powered PDF Data Extraction My role:
AI-Powered PDF Data Extraction My role: AI Data Processing and Extracton Engineer Organizations often struggle to extract structured and useful information from large volumes of unstructured PDF documents. I developed a flexible AI-powered data extraction solution that allows users to define the specific entities and fields they want to retrieve. The system processes different PDF formats, identifies relevant information, and converts it into structured, usable data. The solution reduces manual document processing, improves retrieval accuracy, and can be adapted to different document types and business requirements. A working demo link is attached.
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ML Engineer(2)
Muhammad Danish Nadeem's avatar
Muhammad Danish Nadeem
Lahore, Pakistan
Generative AI Developer
New to Contra
Generative AI Developer
Cover image for Engineered a personalized news recommendation
Engineered a personalized news recommendation system leveraging the Microsoft MIND dataset to deliver highly relevant, user-centric content at scale. The solution models user engagement patterns through collaborative filtering techniques to predict and surface articles aligned with individual reading behavior. It encompasses a complete machine learning pipeline, including data preprocessing, model training, evaluation, and performance validation using click-through-based metrics on real-world interaction data.
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Cover image for This Music Genre Classification System
This Music Genre Classification System features a modern, AI-powered dashboard designed to classify music genres from uploaded audio files. The interface provides a seamless user experience with a drag-and-drop audio upload section, real-time prediction results, confidence score visualization, and probability distribution across multiple genres. The dashboard follows a clean dark-theme design with vibrant purple accents, making it visually appealing while maintaining usability. Users can upload audio files in various formats, view the predicted genre instantly, and analyze model confidence through interactive charts and progress bars. Additional features such as prediction history and workflow guidance enhance transparency and user engagement. Overall, the frontend effectively combines machine learning functionality, intuitive user interaction, and modern UI/UX principles to create a professional music genre classification platform suitable for academic projects, research demonstrations, and production-ready AI applications.
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Cover image for Drug discovery usually takes 10
Drug discovery usually takes 10 to 15 years, our service proposes a way to lower the time and the cost by an estimated ten years, by simulating drug molecule behaviour with protein, docking, to give researchers a tool to speed up clinical trials by instead relying on simualtions
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Cover image for AI-Powered Resume Screening System Tired of
AI-Powered Resume Screening System Tired of manually sifting through hundreds of resumes? This intelligent screening system does the heavy lifting — automatically parsing resumes, extracting key skills, and semantically matching candidates to job descriptions in seconds. 🧠 How It Works The system uses advanced Natural Language Processing (NLP) to deeply understand both resumes and job descriptions — going far beyond simple keyword matching. It calculates semantic similarity using cosine similarity, meaning it understands context, not just words. ⚙️ Key Features 📄 Smart Resume Parsing — Automatically extracts skills, experience, and qualifications from any resume format 🔍 Semantic Job Matching — Matches candidates to roles based on meaning, not just keywords 🏆 Candidate Ranking — Instantly ranks applicants by relevance score 📊 Match Scoring — Clear percentage-based compatibility scores for every candidate 🕳️ Skill Gap Analysis — Identifies exactly what skills a candidate is missing for a role 🚀 Streamlit Dashboard — Clean, interactive UI deployable in one click 🛠️ Tech Stack Python · NLP · Scikit-learn · Cosine Similarity · Streamlit · SpaCy / NLTK 💼 Perfect For HR teams, recruitment agencies, startups, and any business drowning in job applications — this tool cuts screening time by up to 80%. 📈 Results It Delivers ✅ Faster hiring decisions ✅ Bias-reduced candidate evaluation ✅ Clear, data-backed shortlisting ✅ Scalable to thousands of resumes
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ML Engineer(3)
Ihtisham Mehmood's avatar
Ihtisham Mehmood
Multan, Pakistan
Data Analysis & AI: Results-Driven Expertise
Data Analysis & AI: Results-Driven Expertise
Cover image for Deep Learning
Deep Learning
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Cover image for Machine learning
Machine learning
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Cover image for All in one LLM Chatbot
All in one LLM Chatbot
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Cover image for A/B Testing For an E-commerce Store
A/B Testing For an E-commerce Store
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ML Engineer(2)
Sumbal Murtaza's avatar
Sumbal Murtaza
Talagang, Pakistan
FinTech developer building secure, modern web platforms.
New to Contra
FinTech developer building secure, modern web platforms.
Cover image for Overview This project provides an interactive
Overview This project provides an interactive platform for financial data analysis and predictive modeling. Built with Python and Streamlit, it enables users to visualize financial trends and explore machine learning-driven insights through an intuitive, web-based interface. Key Features Data Pipeline: Automated ingestion and cleaning of financial datasets. Feature Engineering: Implementation of financial indicators and technical features to capture market dynamics. Predictive Modeling: A streamlined training and evaluation workflow using robust machine learning algorithms. Interactive Visualization: Real-time dashboards allowing users to experiment with different parameters and model configurations. Technical Workflow Data Loading: Robust ingestion of historical financial data. Preprocessing: Handling missing values, noise reduction, and data normalization. Feature Engineering: Extraction of meaningful market features (e.g., technical indicators, volatility metrics). Model Training & Evaluation: A modular approach to training, testing, and validating model performance using industry-standard metrics. Experience It Live Explore the application and interact with the model here: 👉 Financial ML Dashboard (https://vtt4xouy7ifekdm7s5c4zj.streamlit.app/)
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Cover image for Project Title: Privacy-Preserving Sepsis Prediction
Project Title: Privacy-Preserving Sepsis Prediction Model Role: AI Research Intern The Challenge: Integrating complex Recurrent Neural Network (RNN) architectures within a privacy-preserving Multi-Party Computation (MPC) environment. Addressing the "fixed-point arithmetic" limitations inherent in cryptographic frameworks when handling 48-hour sequential medical data. My Approach: Mentored by a Yale University researcher to bridge the gap between AI and secure cryptographic protocols. Independently engineered custom normalization and clipping techniques to resolve data overflow issues caused by sequential computation loops. Successfully optimized the model for the MIMIC-III dataset, ensuring high-quality, functional code performance. The Outcome: Successfully contributed the finalized research implementation to the official open-source repository. Demonstrated technical maturity in handling complex engineering bottlenecks while adhering to formal research methodologies. Here is my repo link: https://github.com/sum710/sequre
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Cover image for Project Name: Pakistan Street Food
Project Name: Pakistan Street Food Guide Project Overview Designed and developed a multi-page, custom website celebrating the rich culinary heritage and vibrant street food culture of Pakistan. The "Pakistan Street Food Guide" serves as a digital exploration of traditional recipes, local favorites, and the stories behind regional street food vendors. Key Features & Deliverables Custom Multi-Page Architecture: Structured a seamless navigation experience across dedicated sections, including the homepage, a visual Food Gallery, and a Contact portal. Lightweight Front-End Engineering: Built entirely from scratch using clean HTML5, CSS3, and vanilla JavaScript. By avoiding heavy external frameworks, the site maintains rapid load times and a highly optimized codebase. Semantic UI/UX Design: Developed an intuitive, image-focused layout designed to highlight cultural storytelling and visual content effectively across different screen sizes. #html #CSS#Frontend #javascript#webdevelopment
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Cover image for Title: Civitas: Digitizing Community Savings
Title: Civitas: Digitizing Community Savings & Financial Trust with AI Description: Traditional community-based saving groups (committees/ROSCA) have always been built on trust, but they often struggle with manual record-keeping, transparency issues, and security risks. I am excited to share Civitas, a full-stack FinTech solution designed to modernize the committee system. Civitas transforms how communities save and contribute money by blending automated financial management with AI-driven security. Key Features: Digital ROSCA Management: A transparent platform where users can join, track, and manage their committee contributions automatically. AI-Powered Trust Engine: A scoring logic that tracks payment consistency and user reliability, ensuring a safe ecosystem. Payout Security: Payouts are protected with mandatory Two-Factor Authentication (2FA) and Google OAuth integration. Modern Tech Stack: Built with React 19, Supabase Cloud, and AI financial advisors. Why Civitas? In the world of FinTech, trust is everything. Civitas replaces paper-based tracking with a permanent, automated digital ledger, reducing human error and building a stronger, more reliable financial community. Explore the live project here: https://civitas-backend.vercel.app/ I’d love to hear your thoughts on how digital transformation is changing the landscape of community-based finance! #FinTech #WebDevelopment #FullStack #AI #ProductDesign #Civitas #FinancialInclusion
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ML Engineer(2)
Hammad Tahir's avatar
Hammad Tahir
Lahore, Pakistan
AI Developer & ML Engineer: Top-notch Expertise
AI Developer & ML Engineer: Top-notch Expertise
Cover image for Yolo v10 - Object Detection and tracking
Yolo v10 - Object Detection and tracking
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Cover image for AI Agents workflow
AI Agents workflow
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Cover image for Computer Vision - Detection and Segmentation with Yolo V9
Computer Vision - Detection and Segmentation with Yolo V9
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Cover image for RAG (Retrieval Augmented Generation) Pipeline
RAG (Retrieval Augmented Generation) Pipeline
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ML Engineer(5)
Imaad Mahmood's avatar
Imaad Mahmood
Bahawalpur, Pakistan
Data Scientist | Data Analyst | Machine Learning
Data Scientist | Data Analyst | Machine Learning
Cover image for Movie Recommendation System — ML + Live API
Movie Recommendation System — ML + Live API
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Cover image for Enterprise RAG Evaluation Pipeline Project
Enterprise RAG Evaluation Pipeline Project
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Cover image for FinCast Pro Development
FinCast Pro Development
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Cover image for How do you turn $15.9K
How do you turn $15.9K in ad spend into $49.2K in revenue? You stop guessing and start tracking Running paid social campaigns without granular visibility is essentially burning budget. For this Q1 2025 performance tracker, the goal wasn't just to make pretty charts—it was to build an automated, actionable intelligence tool that immediately identifies where marketing dollars are generating the highest return. The Data-Driven Insights: By analyzing over 2.7 million impressions and 1.8 million unique reach, this dashboard uncovered the exact levers driving profitability: 🚀 The ROI Engine: The overarching strategy yielded a highly profitable 3.1 Return on Ad Spend (ROAS). 🏆 Winning Formats: Carousel ads heavily dominated the space, capturing 21.9% of the share, proving that interactive, multi-image formats win the algorithm. 📅 Timing is Everything: Engagement rates spiked massively on Saturdays, reaching near 20%, indicating the optimal window for scaling ad spend. 🎯 Campaign Economics: While "Seasonal Promos" drove the highest total top-line revenue , the "Community" campaigns actually delivered the most efficient ROAS.
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ML Engineer(3)