Build a Simple AI Resume Matching Tool in Python(MVP)

@maxscender

I can help you build this Streamlit MVP. To ensure a functional local setup, I will use `pdfplumber` and `python-docx` for robust text extraction and integrate the Groq API (using the Llama 3 model) to handle the semantic analysis. This avoids complex NLP library overhead while providing high-quality "Missing Skills" detection and interview questions. For the matching logic, I’ll implement a hybrid approach: keyword intersection for the technical score and TF-IDF similarity for the overall match percentage. The code will be structured as a single-file Streamlit application for maximum portability, ensuring it runs immediately via `pip install` without environment configuration issues.

@sekai1116

With eight years of experience in full-stack development, I am confident that I can bring valuable insights and expertise to your project. My proficiency in Python, streamlit, and AI-powered solutions makes me the ideal candidate for developing a resume matching tool with job analysis features. In particular, my extensive experience with NLP will be invaluable for efficient keyword extraction and analysis. Aside from technical skills, I am known for delivering clean and readable code within tight deadlines while still meeting all the required deliverables. I have had practical exposure to developing similar solutions in the past, including generating interview questions based on job descriptions and missing skills. While maintaining simplicity, functionality, and clarity - essential aspects for an MVP - I ensure a seamless integration of all the mentioned features. I understand the budget constraints for a student MVP project like this one. Although affordability is important to you, I can assure that the quality of my work never gets compromised. My previous clients have valued me for my ability to write clean, maintainable code while simultaneously solving complex problems efficiently. I also guarantee clear and timely communication throughout the project to take care of minor adjustments you may require.

@SmartCodeDev

Hello, I have experience building Python and Streamlit based AI tools including resume analysis document parsing and OpenRouter integrations. I can develop your MVP with CV upload keyword matching ATS checks multi job comparison interview prep downloadable reports and instant JD parsing while keeping the code clean lightweight and easy to run locally. The app will support PDF and DOCX parsing dark and light mode responsive UI and optimized OpenRouter free API usage for faster responses. You will receive complete source code requirements file setup instructions and a fully functional localhost ready Streamlit application within your 4 to 5 day timeline. I can also handle minor adjustments during development and maintain clear communication throughout the project.

@toriquldev123

Dear Client, I’m Md Toriqul Islam, an experienced Python developer specializing in Streamlit applications, data processing, and AI integration with over 10 years of software development experience building scalable and clean solutions. I understand you need a lightweight Streamlit MVP that allows CV upload (PDF/DOCX), job description input, keyword matching, missing skills detection, match scoring, and interview question generation using optional Groq API, focusing on simplicity, local execution, and functional Python code. Python, Streamlit, pdfplumber, python-docx, NLP, REST APIs, AI integration, data parsing, keyword extraction, scoring algorithms, Groq API, clean code development. Feel free to share details. I’m ready to build this Streamlit MVP within 4–5 days fast delivery quality. Best regards, Md Toriqul Islam.

@chiragardeshna

Hi there, Strong alignment with this requirement comes from experience building lightweight AI-powered Python tools, Streamlit applications, and resume-analysis workflows focused on clean implementation and fast local execution. Clear understanding of the goal to create a simple locally runnable MVP that uploads resumes, compares them against job descriptions, calculates match scores, identifies missing skills, and generates interview questions. Hands-on expertise with Python, Streamlit, pdfplumber, python-docx, NLP keyword extraction workflows, similarity scoring systems, Groq/OpenAI integrations, and clean MVP-focused application architecture. The implementation approach will focus on readable Python structure, lightweight Streamlit UI, accurate resume parsing, simple keyword-matching logic, interview-question generation, and clean documentation with setup instructions for smooth localhost execution within the 4–5 day timeline. Recent work: https://www.freelancer.com/u/chiragardeshna Regards Chirag

@techsty2014

Hi there, We will build your Streamlit resume matching tool: CV upload, keyword extraction, match scoring, multi-job comparison, ATS check, and interview prep with difficulty levels. For speed, we will cache parsed results and batch OpenRouter calls so the free API tier does not bottleneck the workflow. A couple of quick things to confirm: 1) For the URL parser, do target job sites use JavaScript rendering or static HTML? 2) Should the PDF report include visual elements (charts, badges) or plain text layout? The number quoted here is a starting estimate. The exact cost and timeline will be confirmed after we go through the full scope together. Looking forward to discussing further. Best regards, Faizan

@lakshithap1

As a seasoned Python developer, I'm confident in my ability to meet and exceed your needs for this project. I have experience creating functional, clean code and understand the importance of simplicity while maintaining the necessary functionality. Apart from being proficient in Python, I've also worked with similar technologies you mentioned like streamlit which makes me even more suitable for this job. In past projects, I've tackled various cases of AI/ML development including natural language processing, data extraction and analysis -- all which align with the key features required for your tool. Besides having experience specifically with python-docx and pdfplumber, I’m adaptable & explore new tech when needed to build solutions at the most efficient capacity. I can assure you that my pricing will be competitive, and I work with complete integrity to provide quick turnarounds without compromising on quality. Along those lines, clear communication is my paramount commitment throughout projects. Let’s tap into my strong problem solving skills to quickly produce an MVP that reflects basic resume-job matching as required.

@fantasyinfo

MVP of Resume ATS tracker in python as a backend and grook ai as a code to check i m ready to start over

@mamuncmt

Hello, Please reply i will sent the screenshot already i have I can build this MVP using Python and Streamlit with a clean black-and-white UI. The system will parse PDF/DOCX resumes, extract keywords, compare them with job descriptions, and provide similarity scoring plus missing skill detection using NLP. I can also integrate the OpenRouter API for interview question generation. Thanks, Mamun

@craigd43

Drawing from my extensive experience in Python web development, I am excited about this project as it aligns precisely with my area of expertise. As a passionate developer dedicated to creating tailored and efficient solutions, I can assure you of a simple yet powerful AI resume matching tool. My proficiency in Frontend/backend Streamlit and related technologies gives me a strong command over the tools needed for this project. Additionally, I have hands-on experience with python libraries pdfplumber and python-docx which are crucial for the resume parsing feature. Having worked on similar projects involving data extraction and analysis, I understand the significance of swift delivery without sacrificing quality. This makes me uniquely well-suited to your timeline requirement. Moreover, I can guarantee clean and organized code that's well-commented, making it not only easy for you to understand but easy for other Python developers on your team to maintain. In summary, I not only possess the technological prowess required to accomplish this task but also prioritize strong communication and exceeding expectations. My pricing is competitive yet fair for this student project scope, and I am more than willing to walk you through every step of our journey together. Looking forward to hearing from you soon!

@Web1devloper

As someone with vast experience in full-stack development, including proficiency in Python, I am more than qualified to take on this project. My understanding of the Stack - both frontend & backend along with familiarity with Streamlit and its deployment - will facilitate me to create a cutting-edge MVP that fulfills your requirements. Over the years, I've mastered the art of creating simple yet highly functional applications, which align perfectly with your project vision. Additionally, my ample experience in handling databases and cloud services such as AWS or GCP will aid a smooth implementation. I can develop an easily deployable application that runs locally without complicated setup or APIs if it suits your preferences better. Meeting deadlines is a top priority for me. In line with your expected delivery time, I assure you complete deliverables within 4–5 days of project initiation. Throughout the development process, I maintain clear and efficient communication channels so that we can address any scope change or requests together seamlessly. As a bonus, my rate for this MVP project is highly competitive without compromising on quality or efficiency. Embrace a proficient developer who will transform your academic MVP into reality

@goranm16

Hi, this fits well. I’d keep the MVP simple: upload CV, parse PDF/DOCX, compare it with the job description, show missing skills, match score, and generate 5 interview questions. I’ve built document-processing tools where the key was clean parsing before adding AI. I’d start with reliable keyword matching, then use Groq only if needed. Main risk is messy CV formatting, so I’d add clear fallbacks and readable outputs. Thanks!

@umairinayat1

As an AI/ML Engineer with 3+ years of experience in building complex and high-performance systems, I believe I am the perfect fit for your project. My NLP expertise will ensure the efficient extraction and comparison of keywords from resumes and job descriptions. Additionally, my experience working with File Parsing libraries such as pdfplumber and python-docx guarantee that I am suited to handle resume uploads in PDF or DOCX formats without a hitch. Moreover, my proficiency in deploying models using backend technologies like Streamlit and Python ensures that your platform will be fast, reliable, and user-friendly - key requisites for your project. Importantly, my diverse experience in using AI APIs makes me well-equipped to implement OpenRouter's free API effectively. In conclusion, hiring me guarantees that you are getting the perfect blend of backend proficiency, NLP skills, and a commitment to deploying a smoothly-functioning streamlined web application - just what your project requires. Let my proven track record of delivering exceptional and reliable projects sway you as you make this crucial decision. I look forward to working together on this academic MVP project that prioritizes simplicity, clarity, and functionality above all else.

@jay8mac

Lets chat, a free consultation and no obligation. I understand you need a clean, professional, and user-friendly solution for your "Build a Simple AI Resume Matching Tool in Python(MVP)" project. My skills in PHP, Java, JavaScript are a perfect fit for this project. While I am new to freelancer.com, my extensive experience delivers integrated, automated solutions. Regards, Jason McLachlan

@mickeysz

Hi, I read your job description carefully and got excited. Why? Because I have completed a project totally similar to yours — an AI Resume Analyzer. You can check my reviews and the client's job description. I can help you based on my experience. Hope to work with you. Thank you for reading my proposal. Mickey

@snath88

Hi, Drop me a message — I'll share a quick prototype based on what I understood. If it matches your expectations, we can move forward. Thanks!

@mubashir021

I understand the importance of delivering a simple yet effective MVP for your AI resume matching tool, and I am ready to bring your vision to life. With my experience in Python and Streamlit, I can create a lightweight web application that meets all your specified requirements. I will ensure users can easily upload resumes, paste job descriptions, and receive insightful keyword matching, missing skills detection, and a match score. Additionally, I will implement an interview question generator to enhance user preparation. My focus will be on clean, readable code and a basic functional UI, ensuring a smooth local run without complex setups. I will maintain clear communication throughout the process and provide well-commented source code along with installation instructions. I estimate that I can complete this project in 14 days, allowing ample time for revisions and quality assurance. I look forward to collaborating with you on this exciting project and delivering a tool that meets your academic needs.

@faizak54

Hi, This is a perfect fit — I build exactly these kinds of AI-powered Python tools daily. I'll deliver a fully working Streamlit app with all 14 features: resume upload, keyword matching, match score, ATS check, interview prep, multi-job comparison, learning resources, and downloadable PDF/TXT reports — all powered by OpenRouter free API with speed optimizations. Clean, well-commented code with README and requirements.txt. Ready to run locally in one command. Timeline: 3 days. Can start today. Let's build it!

@aurvix

Your MVP needs a lightweight Streamlit app that turns uploaded CVs and pasted job descriptions into a match score, missing skills, interview questions, and tailored improvement tips — all in one local tool. In the Energy Label Parser project, I built a computer vision + NLP pipeline that extracted structured specs from PDFs with 95% accuracy, using the same text processing patterns. My stack covers Python, Streamlit, scikit-learn for keyword similarity, and Docker for reproducible local runs. I'd deliver this in two milestones: first a working single-job analyzer with keyword matching and scoring, then multi-job comparison with AI-generated suggestions and ranked output. Quick question — for the interview question generator, do you want simple template-based generation from keyword gaps, or a lightweight LLM inference step via Hugging Face?