Resume & Recommendation AI Development

@vishal1145

Your recommendation engine will fail if you're relying on keyword matching alone - most ATS systems miss 40% of qualified candidates because they can't understand semantic similarity between "led a team of 5 engineers" and "managed cross-functional development squad." Before architecting the solution, I need clarity on two things: What's your current applicant volume per month (100 vs 10,000 resumes changes the infrastructure entirely), and does your ATS support bulk API writes or are we limited to single-record POST requests? Here's the architectural approach: - NODE.JS + PDF-PARSE: Build a document ingestion pipeline that handles corrupted files and multi-column layouts without breaking field extraction. - HUGGING FACE TRANSFORMERS: Use sentence-transformers to generate embeddings for job descriptions and resumes, then calculate cosine similarity for matching instead of brittle keyword rules. - VECTOR DATABASE (Pinecone or Weaviate): Store resume embeddings for sub-second similarity searches across your entire candidate pool without re-processing documents. - REACT DASHBOARD: Build an admin panel where you can flag incorrect extractions and retrain the NER model on edge cases your system encounters. - API RATE LIMITING: Implement exponential backoff for ATS writes so bulk uploads don't trigger 429 errors and lose data. I've built 3 similar parsing systems for recruitment platforms that process 50K+ resumes monthly. Let's schedule a 15-minute call to discuss your ATS API documentation and edge cases before I start development.

@himanshus642

As a seasoned Full Stack Developer well-versed in AI automation and intelligent workflows, I believe that I have the perfect blend of skills and experience for your project. Over the course of my 5+ year career, I have successfully crafted numerous AI-driven solutions, financial platforms, and automation systems for businesses across a range of industries. With this background, I'm confident I can build an efficient AI agent for you that seamlessly parses resumes and pushes data into your existing management system via REST API. In terms of matching technology, I have hands-on experience with several popular options such as spaCy, Hugging Face transformers, LangChain and Vector databases. If needed, I can efficiently fine-tune the models to meet your specific requirements and ensure consistent performance over time. By choosing me to undertake this project, not only will you benefit from my proficiency with relevant technologies like Node.js and Python but you'll also have a dedicated professional who aligns technology with your business goals. My milestone-first approach will ensure a steady stream of progress accompanied by clean code, comprehensive setup scripts, and detailed documentation to facilitate retraining or modification of the models as per future needs.

@atech20102018

Hi, Your resume parsing and recommendation platform sounds interesting. We have strong experience building custom web applications, API integrations, data processing workflows, and AI-assisted solutions. The requirements around resume extraction, ATS integration, candidate-role matching, and scalable APIs are well aligned with our expertise. We would be happy to discuss the existing management system APIs, expected data fields, and recommendation logic in more detail. While we do not maintain public repositories for client projects, we can discuss relevant experience and proposed architecture during our conversation. Looking forward to learning more about your requirements.

@nexvative

Hello, I have extensive experience building AI-powered resume parsers, candidate matching systems, and ATS integrations using Python, NLP, LLMs, and REST APIs. I can develop a production-ready solution that automatically extracts structured candidate data from PDF/DOC/DOCX resumes and syncs it directly with your applicant management system. My approach: • Resume parsing using a combination of NLP models, LLMs, and rule-based validation for high extraction accuracy • Extraction of contact details, skills, education, work history, certifications, and custom fields • Automated posting of structured candidate profiles to your ATS via REST API • Recommendation engine using semantic matching, embeddings, and skill-based scoring • Fast API endpoints/webhooks for candidate-to-role and role-to-candidate recommendations • Modular architecture that allows new fields, models, and workflows to be added easily Deliverables: ✔ Resume parsing microservice/API ✔ ATS integration with automatic data synchronization ✔ Candidate recommendation engine ✔ Well-documented source code ✔ Setup scripts and deployment guide ✔ README explaining retraining, fine-tuning, and adding new fields ✔ Accuracy and performance testing reports I have worked on recruitment automation, document intelligence, information extraction, and AI matching solutions. My focus will be achieving high extraction accuracy, reliable ATS integration, and explainable recommendations that recruiters can trust.

@ASSAMWEB

Greetings, I have read the project description I have been working on a similar project in recent time "Resumes Platforms" I am interested in the work open a chat to discuss requirements in details. Live Demo available

@tamannarajput18

My name is Tamanna, and I am an experienced Full Stack Developer with a particular focus on automation using AI tools. I've had successful experiences implementing AI Chatbots, building RESTful APIs, and harnessing the power of Node.js and React.js for efficient and scalable applications. Consequently, streamlining hiring processes by developing an AI-powered resume and recommendation system aligns perfectly with my specialized skill set. With heavyweight understanding of tools like n8n that can optimize business processes and connect multiple platforms through automated pipelines, I'll not only ensure that your resumes are accurately parsed and seamlessly integrated into your applicant-management system, but also provide you a lightweight recommendation engine that fetches potential candidates in <3 seconds per query. Moreover, my expertise with modern databases including MongoDB will ensure your data is reliable, maintainable, and scalable. I'm highly adaptable to different technological stacks like spaCy or Hugging Face transformers too.

@monicasynthesis

Hello, I’ve gone through your requirements and can build an AI-powered resume parsing and candidate matching system integrated with your ATS. With experience in AI automation and API integrations, I can deliver a scalable, accurate solution. What I can help you with: • Resume parsing from PDF, DOC, and DOCX files • ATS REST API integration for automated data flow • AI-based candidate-job matching engine • Clean code, setup scripts, and documentation Warm regards, Monica Bhatia

@manoval09

Hi, Your hiring pipeline is buried in resume processing—you need a way to quickly filter and rank applications without manual review. I can build a parsing system that extracts key data from resumes (skills, experience, education, keywords) and ranks candidates against your pipeline criteria. I'll use Python with spaCy for NLP-based extraction and a rule-based matching engine tuned to your specific scoring rules. This avoids the cost and latency of training a custom model while delivering 80%+ accuracy on structured fields. For the first 24 hours, I'll audit your current resume formats and map out the matching logic that matters most. One quick question: are you scoring candidates primarily on keyword matches, experience duration, education level, or a combination? That determines whether we use rule-based filtering or something more sophisticated. Best regards, Val

@Apponn

Hey there, I reviewed your requirements and understand that you're looking for an AI-powered system that can parse resumes, extract structured candidate data, push it to your ATS via API, and provide intelligent candidate-role recommendations. I specialize in NLP, AI chatbots, LLM integrations, and intelligent automation. I have experience building document-processing pipelines, information extraction systems, and semantic search solutions. My approach would be to combine NLP and LLM-based extraction with a recommendation engine that delivers accurate, explainable matches while ensuring seamless ATS integration and fast response times. I'd be happy to discuss the architecture and share relevant AI/NLP projects. Best regards, Rohit

@cuyodigital

I looked at your resume parsing AI brief and need an agent that extracts contact details, skills, education, employment history from PDF/DOCX files, pushes data via REST API to your applicant system, plus a recommendation engine for matching candidates to roles. I have 5+ years building resume parsing solutions with spaCy and Hugging Face, over 10 projects achieving 95% extraction accuracy. You can see representative examples of my work on my Freelancer profile: https://www.freelancer.com/u/cuyodigital. Deliverables include parsing agent with API, recommendation engine with sub-3 second responses, setup scripts, and retraining documentation. Rate 1000 INR per hour. Duration 30 hours. Will you provide 50 test resumes and the applicant system API documentation? Do you have predefined skill taxonomies or custom fields? Let me know your answers. I can start right away. ricardo PS. Have question on the project and I would like you to check the clarification board

@rahulsimraiya131

Rahul here, I understand you need an AI-powered resume processing system that can extract structured candidate data from resumes, automatically sync it with your applicant management platform, and provide intelligent candidate-role matching recommendations. As a Full Stack Developer with 10+ years of experience, I've built AI-driven automation, document-processing pipelines, REST API integrations, and data-matching systems using Python, NLP frameworks, LLMs, and vector search technologies. My approach is to build a scalable parsing service with high extraction accuracy, automated ATS integration, and a recommendation engine that delivers explainable candidate matching through fast API responses. I'd be happy to discuss your ATS API, data structure, and matching requirements in more detail. Ready to start immediately. Thank you for your consideration.

@toqeer74

Your challenge of automating resume parsing with a seamless integration into your applicant-management system demands an architecture that ensures ≥95% extraction accuracy while facilitating real-time candidate recommendations. Leveraging advanced NLP libraries such as spaCy or Hugging Face transformers can optimize parsing performance, and employing LangChain can enhance contextual understanding for recommendations. Code will be structured with clear setup scripts to enable model retraining, ensuring adaptability over time. Expect the initial deliverable within 14 days. What does success look like for you at the end of this project?

@radheys40

I am Radheshyam K Mohapatra, a passionate Full Stack Developer offering freelance web and software development services. I help startups, businesses, and individuals build powerful digital platforms according to their requirements. My expertise includes website development, custom web applications, backend systems, database management, API integration, and responsive UI development. I focus on delivering high-quality work, timely project completion, and long-term support. Services Website Development Web Application Development Admin Panel Development Custom Software Development E-commerce Website Development API Development & Integration Database Design & Management Frontend UI Development Backend Development Website Maintenance & Bug Fixing Payment Gateway Integration Hosting & Deployment Support Technical Skills Frontend: HTML, CSS, JavaScript, Bootstrap, React Backend: PHP, Laravel, CodeIgniter, Node.js Database: MySQL, MongoDB CMS & E-commerce: WordPress, Shopify Other Skills: REST API, Payment Gateway, Git, Hosting, Server Deployment Why Choose Me? Complete full stack development support Clean and scalable code Mobile-friendly and SEO-friendly websites Custom solutions as per business needs Timely delivery Affordable freelance pricing Long-term technical support

@tyronet2

You need a resume parsing pipeline that extracts structured data from PDF/DOC/DOCX files and pushes it to your ATS via REST API — no manual upload, no lost fields — plus a recommendation engine that surfaces best-fit candidates for a role in under 3 seconds. At Marin Software I built LangChain AI pipelines handling document processing and structured output extraction — the same pattern applies here. Stack I'd use: PyMuPDF + python-docx for file parsing, spaCy for entity extraction (contact details, skills, education, employment history), with a LangChain + OpenAI fallback for edge cases that rule-based extraction misses. Structured data posted to your ATS REST API via a FastAPI microservice. For the recommendation engine: sentence-transformers to embed candidate profiles and job descriptions, FAISS or ChromaDB as the vector store for sub-3-second similarity search. 95% extraction accuracy on a 50-doc test set is achievable with spaCy + LLM fallback combination — pure rule-based approaches struggle with varied resume formats, so the hybrid approach is key. What ATS are you using and does it have documented REST API endpoints?

@jdbsoftech

Hello Dear, I am Jagmohan Kumawat, a multidisciplinary digital expert with 5+ years of experience building luxury websites, mobile apps, digital marketing, automations, intelligent systems and high impact creative assets. My focus is always on delivering results with precision, style and longterm scalability. Signature Excellence • Luxury Websites & Web Systems • iOS & Android Mobile App Development • Custom API Integrations • Advanced Workflow Automation & AI Systems • Salesforce CRM Setup, Flows & Cloud Integrations • Professional Branding & UI/UX • Social Media Content & Digital Strategy • E-Commerce Systems & Automation • Premium Video Creation & Cinematic Editing Technology & Creative Mastery Node.js | React | Laravel | WordPress | PHP | JS | Shopify | Android/iOS | Salesforce Cloud | CRM Automations | REST APIs | Firebase | AI Solutions | Figma | Adobe Suite (Illustrator, Photoshop, Premiere Pro, After Effects) Canva Pro | AutoCAD | Motion Graphics & AI Video | Digital Marketing | Content Writer | SEO/SMO I’m ready to take your project forward with precision, creativity and technical excellence. Feel free to share more details. I will prepare a customize plan for your exact needs. Best Regards Jagmohan Kumawat

@akshayupadhyar

Hi, I can help build an AI-powered resume parsing and recommendation system that accepts PDF/DOC/DOCX resumes, extracts structured candidate data, and pushes it into your existing applicant-management system through REST API. My approach would include: • Resume upload and file processing • PDF/DOC/DOCX parsing • Structured data extraction • Custom field mapping • REST API integration with your applicant system • Candidate-to-role and role-to-candidate matching • API/webhook response for recommendations • Accuracy testing on your 50-document sample set • Clean setup scripts and README documentation For recommendations, I can use embeddings/vector search with a rule-based scoring layer so results are explainable, fast, and easy to adjust over time. I have experience with Node.js, React.js, APIs, automation workflows, OpenAI integrations, AI chatbots, Python integrations, and scalable backend systems. I can also build a lightweight dashboard if you need a review screen for parsed data and match scores. I’ll focus on clean architecture, secure file handling, reliable API posting, and performance so the recommendation response stays under the required time target. Relevant experience includes AI automation systems, CRM automation, API integrations, SaaS platforms, and custom business tools. I’d be happy to review your applicant-management API documentation and sample resumes, then suggest the best technical approach and timeline. Best regards, Akshay

@bansalishika58

Hello, Your project aligns closely with my experience building AI-powered applications and full-stack systems. My proposed approach would be: • Resume Parsing: PDF/DOC/DOCX processing with structured extraction of contact details, skills, education, work experience, and custom fields. • AI Processing: LLM-assisted extraction combined with validation rules to improve accuracy across varying resume formats. • API Integration: Automatic posting of structured candidate data to your existing applicant management system via REST APIs. • Recommendation Engine: Candidate-to-role and role-to-candidate matching using embeddings, semantic search, and configurable scoring logic. • Delivery: Clean code, setup scripts, API documentation, and a concise README. A few questions: 1. Are resumes primarily in English? 2. Will the applicant management system API documentation be available? 3. Do you already have job descriptions available for matching? I have experience developing AI-integrated web applications, REST APIs, authentication systems, and data-driven platforms. I focus on building maintainable solutions that can be improved and tuned over time. I would be happy to discuss architecture options and implementation details. Best regards, Ishika Bansal Full Stack Developer

@kdstechsolution

Hi, I have experience building AI-powered applications, including document parsing, NLP workflows, API integrations, and recommendation systems. I can develop a resume parsing solution that extracts structured candidate data from PDF/DOC/DOCX files, automatically pushes it to your applicant management system, and provides intelligent candidate-role matching with explainable recommendations. The solution will include clean code, setup documentation, and support for future customization and model improvements. Let's connect! Thanks.