LinkedIn Job Search - Mindcase API Documentation

$0.8 / 1k jobs Extract LinkedIn job details — title, company, location, URL — by specifying job titles, location, and filters

Endpoint

POST /api/v1/agents/linkedin/job-search/run

Parameters

array

required

List · Job titles to search for (e.g. ‘product manager’). One per line.

integer

default:50

Number · Jobs to return. Use 0 for all.

array

List · Filter to jobs in these locations. One per line.

array

List · Filter to jobs at these companies (e.g. Google, Stripe). One per line.

array

Multi-select · Filter by where the work happens.Options: remote, hybrid, officeLegend: remote = Remote, hybrid = Hybrid, office = On-site

array

Multi-select · Filter by employment type.Options: full-time, part-time, contract, internship, temporaryLegend: full-time = Full-time, part-time = Part-time, contract = Contract, internship = Internship, temporary = Temporary

array

Multi-select · Filter by required experience level.Options: internship, entry, associate, mid-senior, director, executiveLegend: internship = Internship, entry = Entry level, associate = Associate, mid-senior = Mid-Senior, director = Director, executive = Executive

array

Multi-select · Only jobs paying at least this much (USD).

Show all 9 options

40k+, 60k+, 80k+, 100k+, 120k+, 140k+, 160k+, 180k+, 200k+Legend: 40k+ = $40k+, `60k+` =$ 60k+, 80k+ = $80k+, `100k+` =$ 100k+, 120k+ = $120k+, `140k+` =$ 140k+, 160k+ = $160k+, `180k+` =$ 180k+, 200k+ = $200k+View all 9 as a structured list →

string

Dropdown · Only jobs posted within this time window.Options: 1h, 24h, week, monthLegend: 1h = Past hour, 24h = Past 24 hours, week = Past week, month = Past month

string

Dropdown · Sort order for results.Options: relevance, dateLegend: relevance = Most relevant, date = Most recent

array

Multi-select · Filter by industry.View all 434 options →

boolean

Toggle · Only jobs you can apply to with one click on LinkedIn.

boolean

Toggle · Only low-competition jobs (<10 applicants so far).

Response columns

Field	Display name	Type
`searchQuery`	Search Query	text
`searchLocation`	Search Location	text
`filterCompany`	Filter Company	url
`jobUrl`	Job URL	url
`jobTitle`	Job Title	text
`company`	Company	text
`companyUrl`	Company URL	url
`companyLogo`	Company Logo	url
`industry`	Industry	text
`companySize`	Company Size	number
`companyFollowers`	Company Followers	number
`location`	Location	text
`workMode`	Work Mode	text
`remoteOk`	Remote OK	boolean
`employmentType`	Employment Type	text
`applicants`	Applicants	number
`posted`	Posted	text
`expires`	Expires	text
`new`	New	boolean
`applyUrl`	Apply URL	url
`applyMethod`	Apply Method	text
`limitReached`	Limit Reached	boolean
`state`	State	text
`jobIndustries`	Job Industries	text
`jobFunctions`	Job Functions	text
`description`	Description	text
`headerCaption`	Header Caption	text
`companyBackgroundCover`	Company Background Cover	url
`companyDescription`	Company Description	text
`companyEmployeeCountRangeStart`	Company Employee Count Range Start	integer
`companyIndustriesTitle`	Company Industries Title	text
`companyLocationsCity`	Company Locations City	text
`companyLocationsCountry`	Company Locations Country	text
`companyLocationsGeographicArea`	Company Locations Geographic Area	text
`companyLocationsHeadquarter`	Company Locations Headquarter	boolean
`companySpecialities`	Company Specialities	text
`companyWebsite`	Company Website	url
`locationCountryCode`	Location Country Code	text
`locationCity`	Location City	text
`locationCountry`	Location Country	text
`parsedCountryCode`	Parsed Country Code	text
`locationState`	Location State	text

Example

curl -X POST https://api.mindcase.co/api/v1/agents/linkedin/job-search/run \
  -H "Authorization: Bearer mk_live_abc123def456" \
  -H "Content-Type: application/json" \
  -d '{
  "params": {
    "jobTitles": [
      "AI Engineer"
    ],
    "locations": [
      "San Francisco",
      "New York"
    ],
    "maxResults": 10,
    "company": [
      "https://www.linkedin.com/company/openai"
    ]
  }
}'

import requests

resp = requests.post(
    "https://api.mindcase.co/api/v1/agents/linkedin/job-search/run",
    headers={"Authorization": "Bearer mk_live_abc123def456"},
    json={"params": {
    "jobTitles": [
        "AI Engineer"
    ],
    "locations": [
        "San Francisco",
        "New York"
    ],
    "maxResults": 10,
    "company": [
        "https://www.linkedin.com/company/openai"
    ]
}},
)
data = resp.json()

Example response

Response

{
  "job_id": "job_7f3a2b1c",
  "status": "completed",
  "data": [
    {
      "searchQuery": "AI Engineer",
      "searchLocation": "San Francisco",
      "filterCompany": [
        "https://www.linkedin.com/company/openai"
      ],
      "jobUrl": "https://www.linkedin.com/jobs/view/4318941890/",
      "jobTitle": "Training: ML Framework Engineer",
      "company": "OpenAI",
      "companyUrl": "https://www.linkedin.com/company/openai",
      "companyLogo": "https://media.licdn.com/dms/image/v2/D560BAQHpzXbqSyR74A/company-logo_400_400/B56ZT8EYB8HsAY-/0/1739395793272/openai_logo?e=1779321600&v=beta&t=gIum5j149BuzIqgG-RFQ_tKVsj9mJYS4M4uvdsoH1jw",
      "industry": null,
      "companySize": 8410,
      "companyFollowers": 10823733,
      "location": "San Francisco, CA, United States",
      "workMode": null,
      "remoteOk": false,
      "employmentType": "full_time",
      "applicants": 200,
      "posted": "2026-04-18T12:12:29.000Z",
      "expires": "2026-07-26T03:30:36.000Z",
      "new": false,
      "applyUrl": "https://jobs.ashbyhq.com/openai/d8794980-1d3f-4d82-8b48-811449b6c492?utm_source=8lvZy0eqYJ",
      "applyMethod": "OffsiteApply",
      "limitReached": false,
      "state": "LISTED",
      "jobIndustries": [
        "Research Services"
      ],
      "jobFunctions": [
        "ENG",
        "IT"
      ],
      "description": "About The Team\n\nTraining Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we\u2019re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve.\n\nOur work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes.\n\nWe integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products).\n\nAbout The Role\n\nAs a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward.\n\nWe\u2019re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact.\n\nThis role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.\n\nIn This Role, You Will\n\nApply the latest techniques in our internal training framework to achieve impressive hardware efficiency for our training runsProfile and optimize our training frameworkWork with researchers to enable them to develop the next generation of models\n\nYou Might Thrive In This Role If You\n\nHave run small scale ML experimentsLove figuring out how systems work and continuously come up with ideas for how to make them faster while minimizing complexity and maintenance burdenHave strong software engineering skills and are proficient in Python\n\nAbout OpenAI\n\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.\n\nWe are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.\n\nFor additional information, please see OpenAI\u2019s Affirmative Action and Equal Employment Opportunity Policy Statement.\n\nBackground checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.\n\nTo notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.\n\nWe are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.\n\nOpenAI Global Applicant Privacy Policy\n\nAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.",
      "headerCaption": "OpenAI\nSan Francisco, CA\n1 week ago\nOver 200 applicants\nSee who OpenAI has hired for this role",
      "companyBackgroundCover": "https://media.licdn.com/dms/image/v2/D563DAQEiLbFUDLFr1g/image-scale_191_1128/image-scale_191_1128/0/1737585072384/openai_cover?e=1778310000&v=beta&t=H36dX1k1WzGUqlxiCDs7LaAo6aU3xOfwLpKobasKB9o",
      "companyDescription": "OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. AI is an extremely powerful tool that must be created with safety and human needs at its core. OpenAI is dedicated to putting that alignment of interests first \u2014 ahead of profit.\n\nTo achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. Our investment in diversity, equity, and inclusion is ongoing, executed through a wide range of initiatives, and championed and supported by leadership.\n\nAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.",
      "companyEmployeeCountRangeStart": 1001,
      "companyIndustriesTitle": null,
      "companyLocationsCity": null,
      "companyLocationsCountry": null,
      "companyLocationsGeographicArea": null,
      "companyLocationsHeadquarter": null,
      "companySpecialities": [
        "artificial intelligence",
        "machine learning"
      ],
      "companyWebsite": "https://openai.com/",
      "locationCountryCode": "us",
      "locationCity": "San Francisco",
      "locationCountry": "United States",
      "parsedCountryCode": "US",
      "locationState": "California"
    }
  ]
}

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