LinkedIn Job Details Scraper – Descriptions & Data

Turn known LinkedIn vacancies into detailed job records. LinkedIn Job Details Scraper extracts public descriptions, employer information, hiring criteria, application links, and salary or benefits fields when the listing exposes them.

Submit job URLs or numeric IDs to enrich a shortlist, analyze requirements, or add readable descriptions to a vacancy database. Each unique job produces one row, with its details available in the same table and JSON export.

At a glance	Details
📥 Input	LinkedIn job URLs or numeric job IDs
📤 Output	Descriptions, employer, location, criteria, application details, and available compensation
🧩 Format	One row per unique processed job ID
🔐 Login required	No LinkedIn credentials or cookies
💾 Delivery	Apify dataset for JSON, spreadsheet exports, and API access

What the LinkedIn job details scraper extracts 💼

The Actor reads the public job page and returns:

• Job ID, canonical URL, title, and employer identity
• Plain-text and HTML descriptions
• Location, available address details, and workplace type
• Posting date, relative posting text, and closing date when published
• Applicant text and a parsed count, plus the observed open or closed status
• Application URL, seniority, employment type, job function, and industry
• Qualifications, skills, benefits, and published salary fields
• The original labels and values from the job's criteria section

Optional fields depend on what the public listing supplies. A successful row can therefore have a complete description while salary, skills, address, or application details remain empty.

How to scrape LinkedIn job details 🚀

1. Add a LinkedIn job URL or numeric job ID for each vacancy.
2. Start the Actor.
3. Review the success and failed rows in the dataset.
4. Export the records or join them to job-search results by id.

{
  "inputList": [
    "https://www.linkedin.com/jobs/view/4378357766/"
  ]
}

The Actor also accepts LinkedIn jobs URLs containing currentJobId. Different accepted URLs that resolve to the same numeric job ID are processed once.

Job detail fields and output 📦

Field group	Included data
Identity	Input, status, job ID, URL, and title
Employer and place	Company identity, logo, location, address, and workplace type
Description	Text, HTML, qualifications, skills, and benefits
Timing and applications	Posting dates, applicant text and count, job status, and application URL
Hiring criteria	Seniority, employment type, function, industry, and paired criteria labels and values
Compensation	Currency, single value or range, and pay period when published

Complete illustrative output item with all 39 fields. The vacancy, employer, dates, and compensation below are fictional examples, not a live result:

{
  "input": "9876543210",
  "status": "success",
  "id": "9876543210",
  "url": "https://www.linkedin.com/jobs/view/9876543210/",
  "title": "Software Engineer",
  "company.id": "12345678",
  "company.name": "Example Analytics",
  "company.url": "https://www.linkedin.com/company/example-analytics/",
  "company.logo": "https://example.com/company-logo.png",
  "location": "Singapore",
  "address.street": "",
  "address.city": "Singapore",
  "address.region": "",
  "address.postal_code": "",
  "address.country": "SG",
  "workplace_type": "Hybrid",
  "description": "Build data services and reliable internal tools. Experience with Python and SQL is required.",
  "description_html": "<p>Build data services and reliable internal tools. Experience with Python and SQL is required.</p>",
  "posted_at": "2026-09-06",
  "posted_time": "2 days ago",
  "valid_through": "2026-10-06",
  "applicants_text": "32 applicants",
  "applicants": 32,
  "job_status": "open",
  "apply_url": "https://example.com/careers/software-engineer",
  "seniority_level": "Mid-Senior level",
  "employment_type": "Full-time",
  "job_function": "Engineering",
  "industries": "Software Development",
  "qualifications": "Experience building production software with Python and SQL.",
  "skills": [
    "Python",
    "SQL"
  ],
  "benefits": [
    "Medical insurance",
    "Learning budget"
  ],
  "salary.currency": "SGD",
  "salary.value": 0,
  "salary.min": 90000,
  "salary.max": 120000,
  "salary.unit": "YEAR",
  "criteria.name": [
    "Seniority level",
    "Employment type",
    "Job function",
    "Industries"
  ],
  "criteria.value": [
    "Mid-Senior level",
    "Full-time",
    "Engineering",
    "Software Development"
  ]
}

One job occupies one row in one table. JSON keys such as company.name and salary.min are literal field names matching the columns. The entries in criteria.name and criteria.value match by position; skills and benefits remain lists in the same row.

Successful results preserve empty strings, empty lists, and default numeric values when the public page omits information. In particular, 0 in an applicant or salary field can mean no value was supplied, not a verified zero. A failed result retains input, sets status to failed, and uses null for all job-data fields.

Input requirements and job coverage ⚙️

Parameter	Type	Required	Rules
inputList	array of strings	Yes	At least one LinkedIn job URL or numeric job ID

Accepted forms include 4378357766, https://www.linkedin.com/jobs/view/4378357766/, and https://www.linkedin.com/jobs/search/?currentJobId=4378357766. Numeric IDs must contain at least six digits. Full URLs must use HTTP or HTTPS on LinkedIn and identify a job within a jobs path.

There is no pagination setting: each accepted target refers to one vacancy. Collect IDs with Job Search Scraper or Company Jobs Scraper before using this Actor to enrich them.

Closed jobs can still produce a successful detail row if LinkedIn exposes their content. Deleted, restricted, or otherwise unavailable pages can produce failed rows. Neither a valid URL nor a successful response guarantees every optional field.

LinkedIn job details use cases 🎯

Vacancy database enrichment

Add descriptions, application links, and employer details to job IDs collected from search or company listings.

Skills and requirements research

Analyze the description alongside published skills, qualifications, and hiring criteria to compare requirements across roles.

Compensation research

Collect published salary values with their currency and period. Separate absent values before aggregating ranges or comparing employers.

Application workflow preparation

Organize a shortlist with role descriptions, location, public application links, and the observed listing status.

Pricing and billable job rows 💰

Check the Actor's Pricing tab for the current charging model and rate.

Under dataset-item pricing, each saved success or failed row can count as one result. Accepted inputs that resolve to the same job ID are processed once, and automatic request retries do not independently create extra rows.

Descriptions, criteria, skills, and benefits remain inside the job row. They do not create separate dataset items.

LinkedIn job details API and integrations 🔌

Set $ACTOR_ID to the ID shown in the Actor's API tab and $APIFY_TOKEN to your Apify token:

curl -X POST "https://api.apify.com/v2/acts/$ACTOR_ID/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"inputList":["https://www.linkedin.com/jobs/view/4378357766/"]}'

Call the Actor from REST, Apify client libraries, schedules, or webhooks. Send its default dataset to Google Sheets, Make, Zapier, a research database, or your own application. Use job IDs to join detailed records to the listings that selected them.

Reliability and public listing limits ⚠️

The Actor processes up to five requests concurrently and retries temporary request failures. Individual invalid or unavailable jobs are saved as failed rows so other jobs in a mixed batch can continue.

Applicant text may be approximate, and its parsed count should be read together with the original text. The open or closed label reflects the page's visible closure signal; it is not confirmation that the employer is still accepting applications.

LinkedIn can remove listings, restrict public access, or change the fields it exposes. Image and application URLs can change, and optional compensation or criteria fields may be absent. An inability to save the dataset can stop the run.

Frequently asked questions ❓

Can I submit IDs returned by Job Search Scraper?

Yes. Use its job IDs or URLs in inputList. Company Jobs Scraper results can be enriched in the same way.

Does it always return a salary?

Salary fields are populated when published in the data available to the Actor. Missing numeric values can be 0; do not interpret them as a salary offer.

Can it retrieve closed jobs?

Yes, if the public job details remain accessible. The row can succeed with job_status set to closed. Removed or inaccessible listings may fail.

Is the applicant count exact?

The Actor preserves applicant text and parses a number from it. If LinkedIn uses a phrase such as “over 100 applicants,” the number retains that limitation.

Does it require LinkedIn login?

No LinkedIn account, password, or session cookies are required.

Support, responsible use, and related actors 🛟

For a reproducible problem, share the run ID, a public job URL or ID, and the field or behavior you expected through the Actor's support channel.

Use public listing content in accordance with applicable copyright, privacy, contractual, and platform requirements.