LinkedIn Jobs Scraper 💼 (No Cookies)

Scrape LinkedIn job postings from any jobs search URL — no login, no cookies. Get job title, company (with logo, website, description & employee count), location, posted date, salary, benefits, seniority, employment type, function, industries, applicant count and the full job description (HTML + text).

🇬🇧 English · 🇧🇷 Português · 🇪🇸 Español

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Why this scraper?

• 💸 60% cheaper than the alternatives — $0.40 per 1,000 jobs, one flat price, no add-ons.
• 🍪 No cookies, no login — reads LinkedIn's public jobs data over plain HTTP.
• ⚡ Fast & low-cost — no browser.
• 🔎 Respects your search filters — date posted, remote, experience level, job type… whatever is in your search URL.
• 🌎 Trilingual docs — English, Portuguese, Spanish.

Input

Field	Type	Description
searchUrls	array	LinkedIn jobs search URLs (linkedin.com/jobs/search/?keywords=...&location=...). All URL filters are respected.
keywords	string	Simple keyword search (used if no URL is given).
location	string	Location for the keyword search.
count	integer	Max jobs to scrape. Default 100.
scrapeJobDetails	boolean	Fetch each job's full description (HTML + text), seniority, type, function, industries, salary & applicant count. Default true.
scrapeCompany	boolean	Also fetch each company's page (description, website, employee count). Deduplicated per company. Default true.
proxyConfiguration	object	Proxy settings. Datacenter (default) is cheapest and works well.

Example input

{
    "searchUrls": ["https://www.linkedin.com/jobs/search/?keywords=software%20engineer&location=United%20States"],
    "count": 100,
    "scrapeJobDetails": true,
    "scrapeCompany": true,
    "proxyConfiguration": { "useApifyProxy": true }
}

Output

Each job posting is one dataset item:

{
    "id": "4443011652",
    "link": "https://www.linkedin.com/jobs/view/4443011652",
    "title": "Marketing Data Scientist, Measurement & Experimentation",
    "companyName": "LinkedIn",
    "companyLinkedinUrl": "https://www.linkedin.com/company/linkedin",
    "companyLogo": "https://media.licdn.com/dms/image/.../company-logo_100_100/...",
    "location": "New York, NY",
    "postedAt": "2026-07-20",
    "postedAtTimestamp": 1784678400000,
    "benefits": ["Actively Hiring"],
    "salaryInfo": ["$120,000.00/yr", "$180,000.00/yr"],
    "seniorityLevel": "Mid-Senior level",
    "employmentType": "Full-time",
    "jobFunction": "Sales",
    "industries": "Technology, Information and Internet",
    "workplaceType": "Hybrid",
    "applicantsCount": "Over 200 applicants",
    "descriptionHtml": "<p>About the team ...</p>",
    "descriptionText": "About the team ...",
    "applyUrl": "https://www.linkedin.com/jobs/view/4443011652",
    "jobPosterName": null,
    "jobPosterTitle": null,
    "jobPosterPhoto": null,
    "jobPosterProfileUrl": null,
    "companyDescription": "LinkedIn is the world's largest professional network ...",
    "companyWebsite": "https://linkedin.com",
    "companyEmployeesCount": 25000,
    "companySlogan": "Welcome to your professional community.",
    "detailsScraped": true,
    "scrapedAt": "2026-07-28T14:00:00.000Z"
}

Output fields

Field	Notes
id, link, title	Job identifier, URL and title.
companyName, companyLinkedinUrl, companyLogo	Company basics (from the job card).
location, postedAt, postedAtTimestamp	Location and posting date (string + epoch ms).
benefits, salaryInfo	Benefit badges and salary range when LinkedIn shows them.
seniorityLevel, employmentType, jobFunction, industries, workplaceType	Job criteria (needs scrapeJobDetails).
applicantsCount, descriptionHtml, descriptionText	Applicant count and description in HTML and plain text.
companyDescription, companyWebsite, companyEmployeesCount, companySlogan	Company details (needs scrapeCompany).
applyUrl, jobPoster*	Best-effort — LinkedIn hides these behind a sign-in wall on the public page, so they are often null.

ℹ️ salaryInfo, workplaceType, applyUrl and the jobPoster* fields depend on what LinkedIn exposes publicly for each posting and are frequently empty — this is a limit of cookie-free scraping, not a bug.

💰 Cost example

Event	Price
Actor start	$0.001 per run
Job scraped	$0.0004 per job ($0.40 / 1,000)

Scraping 1,000 jobs → 1 × $0.001 + 1,000 × $0.0004 = ≈ $0.40 total.

How to get a search URL

Go to LinkedIn Jobs, search and apply any filters you want, then copy the URL from your browser. Paste it into searchUrls.

FAQ

Does it need my LinkedIn cookie or login? No. It reads only public job-search data.

Can I use my existing search filters? Yes — any filter in the search URL (date posted, remote/on-site, experience level, job type, company) is respected.

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🇧🇷 Português (Brasil)

Extraia vagas do LinkedIn de qualquer URL de busca — sem login, sem cookies. Obtenha título, empresa, local, data, senioridade, tipo de contratação, função, setores e a descrição completa.

Por que este scraper?

• 💸 60% mais barato que as alternativas — $0,40 por 1.000 vagas, preço único, sem add-ons.
• 🍪 Sem cookies, sem login — lê dados públicos de vagas via HTTP.
• ⚡ Rápido e barato — sem navegador.
• 🔎 Respeita seus filtros de busca — data, remoto, senioridade, tipo… o que estiver na URL.
• 🌎 Documentação trilíngue.

Entrada

Campo	Tipo	Descrição
searchUrls	array	URLs de busca de vagas do LinkedIn. Todos os filtros da URL são respeitados.
keywords	string	Busca simples por palavra-chave (se não passar URL).
location	string	Local para a busca por palavra-chave.
count	integer	Máximo de vagas. Padrão 100.
scrapeJobDetails	boolean	Buscar descrição (HTML + texto), senioridade/tipo/função/setores, salário e nº de candidatos. Padrão true.
scrapeCompany	boolean	Buscar também dados da empresa (descrição, site, nº de funcionários). Deduplicado por empresa. Padrão true.
proxyConfiguration	object	Proxy. Datacenter (padrão) é o mais barato.

ℹ️ Campos salaryInfo, workplaceType, applyUrl e jobPoster* dependem do que o LinkedIn expõe publicamente por vaga e às vezes vêm vazios — limite do scraping sem cookies, não é bug.

💰 Exemplo de custo

Evento	Preço
Início do actor	$0,001 por execução
Vaga extraída	$0,0004 por vaga ($0,40 / 1.000)

Extrair 1.000 vagas → 1 × $0,001 + 1.000 × $0,0004 = ≈ $0,40 no total.

Como obter a URL de busca

Vá ao LinkedIn Vagas, busque e aplique os filtros que quiser, copie a URL do navegador e cole em searchUrls.

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🇪🇸 Español

Extrae ofertas de empleo de LinkedIn desde cualquier URL de búsqueda — sin inicio de sesión, sin cookies. Obtén título, empresa, ubicación, fecha, nivel de experiencia, tipo de empleo, función, sectores y la descripción completa.

¿Por qué este scraper?

• 💸 60% más barato que las alternativas — $0,40 por cada 1.000 empleos, precio único, sin cargos ocultos.
• 🍪 Sin cookies, sin inicio de sesión — lee datos públicos de empleos por HTTP.
• ⚡ Rápido y económico — sin navegador.
• 🔎 Respeta tus filtros de búsqueda — fecha, remoto, nivel, tipo… lo que esté en la URL.
• 🌎 Documentación trilingüe.

Entrada

Campo	Tipo	Descripción
searchUrls	array	URLs de búsqueda de empleos de LinkedIn. Se respetan todos los filtros de la URL.
keywords	string	Búsqueda simple por palabra clave (si no das URL).
location	string	Ubicación para la búsqueda por palabra clave.
count	integer	Máximo de empleos. Predeterminado 100.
scrapeJobDetails	boolean	Obtener descripción (HTML + texto), nivel/tipo/función/sectores, salario y nº de candidatos. Predeterminado true.
scrapeCompany	boolean	Obtener también datos de la empresa (descripción, sitio web, nº de empleados). Deduplicado por empresa. Predeterminado true.
proxyConfiguration	object	Proxy. Datacenter (predeterminado) es el más económico.

ℹ️ Los campos salaryInfo, workplaceType, applyUrl y jobPoster* dependen de lo que LinkedIn expone públicamente por oferta y a veces vienen vacíos — límite del scraping sin cookies, no es un error.

💰 Ejemplo de costo

Evento	Precio
Inicio del actor	$0,001 por ejecución
Empleo extraído	$0,0004 por empleo ($0,40 / 1.000)

Extraer 1.000 empleos → 1 × $0,001 + 1.000 × $0,0004 = ≈ $0,40 en total.

Cómo obtener la URL de búsqueda

Ve a LinkedIn Empleos, busca y aplica los filtros que quieras, copia la URL del navegador y pégala en searchUrls.