LinkedIn Job Scraper Development

@Microlent

Your requirement is clear. You need a reliable LinkedIn job scraping solution that accepts location, time range, and work type as runtime parameters, then exports structured job data into both CSV and JSON formats. I have experience building data extraction and automation tools using Python, Selenium, Playwright, BeautifulSoup, and API-based integrations. For this project, I would recommend a Python-based solution with configurable CLI parameters, robust pagination handling, retry logic, and structured exports. The scraper will support: • Location, date range, and work type filters • Job title, company, job URL, description, experience level, job type, and salary extraction when available • CSV and JSON output generation • Command-line execution with no code modifications required • Clean, documented source code and setup guide We have delivered several scraping and data automation solutions involving job portals, business directories, CRM enrichment, and large-scale data collection workflows. Relevant experience: • Web scraping and automation tools • LinkedIn-style data extraction workflows • Python, Selenium, Playwright, BeautifulSoup • CSV, JSON, Excel and database exports • API integrations and data pipelines I can start immediately and provide an initial working version quickly for review. Best regards, Rajesh Rolen

@imraz2016

HI there already i have checked project details job is clear so please contact me then i will show you sample, thank you

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a LinkedIn Job Scraper for Fresh Job Postings ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for a dependable script to pull job postings from LinkedIn. You don't need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for web scraping. I will create a script that meets your needs using efficient methods to ensure you get accurate results within your budget. ➡️ Why Me? I can easily build your job scraper as I have 5 years of experience in web scraping and automation. My expertise includes Python, BeautifulSoup, and Selenium for data extraction, along with strong skills in data handling and output formatting. I ensure my solutions are user-friendly and meet your requirements precisely. ➡️ Let's have a quick chat to discuss your project in detail. I can also share samples of my previous work to demonstrate my capabilities. Looking forward to discussing this with you! ➡️ Skills & Experience: ✅ Web Scraping ✅ Python Programming ✅ BeautifulSoup ✅ Selenium ✅ Data Extraction ✅ CSV/JSON Output ✅ Script Automation ✅ Command Line Tools ✅ Data Structuring ✅ Error Handling ✅ API Integration ✅ Documentation Writing Waiting for your response! Best Regards, Zohaib

@techplusintl

Hi there, ★★★ Python Expert ★★★ 6+ Years of Experience ★★★ I can create a dependable script that pulls job postings from LinkedIn based on your specified inputs. I will use Python with BeautifulSoup or Selenium to build the scraper. The script will accept location, time filter, and work type as parameters without needing code changes. It will output structured records in both CSV and JSON formats. The deliverables will include fully commented source code, a README with setup instructions, and sample output to ensure the data is captured correctly. Questions: 1. Are there any specific regions you want to prioritize for testing? 2. Do you have any preferred libraries or frameworks for the implementation? 3. What is the expected frequency of running this script? Ready to get started!

@a4logic

With your project's specifications and my team at Our Software's expertise, developing a robust and dependable LinkedIn Job Scraper that meets your exact needs is within our realm of proficiency. Drawing from years of experience in web design, development, and SEO services that include working with complex web scrapers; we'll deliver fully commented source code for easy comprehension, set-up steps that are simple to follow in the README file, and the required clean CSV and JSON files as output. Our technological stack preference lies with Python using BeautifulSoup/Selenium given its ability to create tailored solutions efficiently. Nonetheless, we are open to adopting alternatives should they be better suited to your specific demands. Nonce our solution has been implemented on your machine, you'll be able to effortlessly pull fresh job postings from LinkedIn directly based on your unique criteria. We're confident in our ability to present you a structured record containing all match listings: from job link to job title, company name, full job description, salary information when available, experience level, and job type—at least 90% of populated rows—ensuring comprehensive coverage for your needs.

@hiberokpars

Hello! I will create a PHP script to scrape data you need I have extensive experience in writing PHP scripts for data scraping Please see my reviews for reference.

@dfordesigners

Hi, there. I have carefully reviewed the technical issues you are currently facing with LinkedIn Job Scraper Development. When a system is unstable or experiencing downtime, I know that speed and accuracy are your top priorities. My team and I specialize in high level technical support and system recovery. We have helped other businesses in Italy resolve critical issues ranging from database failures and security vulnerabilities to server side performance bottlenecks. We do not believe in applying temporary patches; we focus on performing a root cause analysis to ensure that the problem is solved permanently so your business operations can remain stable. Our goal is to stabilize your environment while ensuring that your data integrity remains the top priority throughout the process. To help me begin the diagnostic process immediately, I have one quick question: Have you made any recent changes to your server configuration, plugins, or third party integrations that might have triggered this issue? Knowing this helps me narrow down the scope of the fix and get your system back online as quickly as possible. I am available to start the diagnostic process immediately if you are ready to proceed. Best regards Kausar and the Team

@AvinaHSinha7

Hi, I can build a clean, CLI-based job scraper that pulls LinkedIn listings based on your runtime filters and exports structured CSV/JSON outputs. I have experience building Python-based scrapers using Selenium/Playwright with dynamic filtering, pagination handling, and structured data extraction. For your project, I will: • Build a CLI script that accepts location, time range, and work type as inputs • Extract job title, company, link, description, salary (when available), experience level, and job type • Handle pagination and dynamic loading reliably • Export clean CSV and JSON files automatically • Ensure the script is fully commented and easy to maintain • Provide a README with setup, usage examples, and environment config I will ensure the solution is stable, reusable, and runs with a single command as requested. I can start immediately. Best regards, Avinash

@Rapha

Hi! My name is Rafael, I'm an automation architect. I can help automate the report, organize the data sources, and leave a simple flow you can run and review whenever needed. Please contact me through chat so we can review the details, confirm the real scope, and estimate timing and cost properly.

@toriquldev123

Hello dear! I’m Md. Toriqul Islam, an experienced Python developer with 10+ years of expertise in web scraping, browser automation, data extraction, and API-driven applications. I’m excited to partner with you and can start immediately. I understand you need a command-line scraper that collects LinkedIn job listings based on location, time filter, and work type, then exports structured CSV and JSON outputs. I have experience building reliable data extraction tools with configurable filters, automated browsers, structured reporting, and well-documented code for easy deployment and maintenance. I have rich experience in Python, Selenium, Playwright, BeautifulSoup, JSON, and CSV processing. I am skilled in building scalable, accurate, and maintainable scraping solutions. I’m ready to deliver fully commented source code, sample outputs, and a detailed README with setup and usage instructions. Looking forward to hearing from you. Best regards, Md. Toriqul Islam

@trm66614

I will build a dependable CLI-driven LinkedIn scraper that accepts location, time filter, and work type at runtime and outputs clean CSV and JSON in the working folder, with full comments. Using BeautifulSoup and Selenium, I’ll reliably collect job link, title, company, full description, salary (when shown), experience level, and type, then save both CSV and JSON. How will you handle site rate limits and retries to keep runs smooth across regions? Would you like an optional dry-run mode to preview data before saving? What level of logging and error reporting do you expect for run-time failures? Do you prefer rotating proxies or a single stable IP for long-term scraping, and are there any region-specific constraints to consider? I’ll provide a README with setup steps, and sample outputs so you can run it on different regions. Deliverables include fully commented source, README, and sample output.

@mayankinnovative

Hello, Your requirements are clear, and I can build a reliable command-line solution that accepts location, time filter, and work type as runtime parameters, then returns structured job data in both CSV and JSON formats without requiring any code changes. My focus will be on creating a maintainable, well-documented scraper with clean output, strong error handling, and a simple user experience. The script will collect job title, company name, job link, description, experience level, job type, and salary information whenever it is available in the source data. The solution will be organized with reusable modules, detailed comments, and a clear README covering installation, configuration, usage examples, and output structure. I will also include sample datasets and validation steps so you can quickly verify results on your own machine. Beyond functionality, I pay close attention to data quality, deduplication, logging, and output consistency to maximize the percentage of fully populated records. I have experience building data extraction, automation, and structured data processing solutions using Python and browser automation frameworks. Examples: on request. Before starting, I'd like to confirm the expected volume of listings per run and whether authenticated access will be available if required for certain job details.

@sharmin283

As a full-stack developer with extensive experience in both traditional web development and modern AI engineering, I believe I am uniquely qualified to take on your LinkedIn Job Scraper project. Python and Node.js are two of my core programming languages, and I have a thorough command over libraries like BeautifulSoup, Selenium, and Puppeteer - perfect for implementing the web scraping side of things. I have an eye for detail and am well-acquainted with producing clean CSV and JSON files. But what really sets me apart is my broader skillset that includes designing fully functional products from scratch – entirely aligned with what you are seeking. Whether it's setting up a dynamic command line interface or ensuring the flexibility to handle runtime parameters without code edits, I'm adept at delivering streamlined solutions that match your specific project needs. In addition to my technical proficiencies, I take immense pride in my excellent work ethic, dedication, and timeliness. Rest assured, when you choose me for this project, you will be guaranteed not just a reliable job scraper but also a long-term partner who is always willing to help.

@krupnovdenis

Hello! We can build a reliable LinkedIn job scraping script for your current task. 1. Do you need the script to work without LinkedIn login, or can it use an authenticated session? 2. Which environment should it run on your side: Python or Node.js? — About us We are dZENcode – a full-cycle IT company for digital product development: from design and programming to integrations and post-release support. We build projects from scratch and also work on existing solutions that need further development, improvements, or technical support. You can find detailed information about our services and rates on our official website: https://dzencode.com. Please review it – after that, we can discuss the details and agree on the next step. ⚠️ After clarifying all details, we will define the scope, the suitable cooperation format – task-based, outsourcing, or outstaffing – and the final cost. Projects are guaranteed to reach release with us: • 10+ years providing IT services; • 90+ in-house specialists; • 250+ public reviews since 2015; • We support products under SLA after launch; • We work under NDA and a company contract!

@amrkhaled32

Hi there, You want a script that walks into LinkedIn, asks the right questions, and comes back with the evidence: job title, company, description, salary, experience level, job type, and the link—all neatly packaged in CSV and JSON. That's exactly the kind of case I take. I'm a Python developer with extensive experience in web automation, scraping, Selenium, API integrations, and data extraction. For this project, I'd build a command-line tool that accepts: Location Time filter (24h / week / month / all) Work type (remote / full-time / part-time / etc.) without requiring any code changes. What you'll get ✔ Command-line execution with a single command ✔ Runtime parameters for all filters ✔ CSV export ✔ JSON export ✔ Extraction of: Job link Job title Company name Full job description Salary (when available) Experience level Employment type ✔ Clean, commented source code ✔ Detailed README with setup and usage examples ✔ Sample output files for verification Technical approach I'll use Python with Selenium (and supporting parsing libraries where beneficial) to ensure reliable extraction of dynamically loaded LinkedIn content. The scraper will include handling for pagination, lazy-loaded descriptions, and data cleaning to maximize field completion rates. Sincerely, Rawan

@demivision

Hi there, Thank you for sharing your requirements for the LinkedIn Job Scraper Development project. My name is DemiVision LLC, and our team specializes in delivering robust, reliable web scraping solutions tailored to our clients’ exact needs. We have carefully reviewed your requirements and understand that you need a command-line tool that takes location, time filter, and work type as runtime inputs, then scrapes fresh job postings from LinkedIn and outputs structured CSV and JSON files. You’ve also specified the need to capture essential fields such as job link, title, company, description, salary, experience level, and job type—with a high level of data completeness. Our team has extensive experience building custom scrapers using both Python (with Selenium/BeautifulSoup) and Node.js (with Puppeteer). We have developed similar solutions for major job boards and social platforms, ensuring data accuracy and resilience against site changes. We also have hands-on expertise in handling dynamic content, login/authentication (when needed), and exporting clean, well-structured data. For your project, our proposed approach is to use Python with Selenium for robust interaction with LinkedIn’s dynamic interface, paired with BeautifulSoup for precise data extraction. The script will be fully parameterized to accept your chosen filters at runtime, requiring no code modifications. Output files will be generated in both CSV and JSON formats as specified. We will ensure the code is clean, well-commented, and accompanied by a comprehensive README and sample outputs. We are committed to delivering a dependable tool that meets your expectations and is easy to run and maintain. Please let us know if you have any preferences regarding technology stack or if you’d like to discuss specific requirements further. Looking forward to collaborating with you! Best regards, The DemiVision LLC Team

@durgesh8527

I've looked over the project details and I'm confident my team is perfect for the job. With a diverse skill set that includes JSON, Node.js, Python and Software Architecture, we can deliver a polished and robust solution tailored to your LinkedIn job scraping needs. Having led similar projects in the past, we recognize the importance of delivering a tool that operates seamlessly on your machine without any code edits—a one-step command line operation. And that's precisely what we'll provide! What sets us apart from other bidders is our 12 years' experience delivering enterprise-grade solutions. We're not just about putting together code; we're about creating fine-tuned systems that tackle real-world problems effectively. We pledge to provide fully commented source code, comprehensive setup steps in a README, and—most importantly—output clean CSV and JSON files in working order so you can effortlessly browse through the scraped data.

@albertc1996

Hi, I’ll build a compact script that pulls LinkedIn jobs using your three inputs (location, time filter, work type) and spits out clean CSV/JSON with all the fields you listed—title, company, description, salary, etc. Single command, no code edits, runs on your machine. I’ll test it across different regions to make sure you’re getting 90%+ populated rows. Commented code, README, and sample output included. Quick, dependable, and ready to use.

@akkiwadhwa1995

Experienced AI Engineer specializing in building intelligent, production-ready LLM-powered applications. Proficient in designing and implementing Retrieval-Augmented Generation (RAG) pipelines using LangChain and LlamaIndex, with hands-on expertise in vector databases such as Pinecone, Weaviate, ChromaDB, and FAISS. Skilled in fine-tuning and deploying large language models (OpenAI, Anthropic, Hugging Face), embedding models, and building semantic search systems. Strong foundation in Python, FastAPI, and cloud infrastructure to deliver scalable AI solutions. Adept at integrating LLM workflows into real-world applications — from intelligent chatbots and document Q&A systems to autonomous AI agents — turning complex AI capabilities into reliable, user-facing products.