> ## Documentation Index > Fetch the complete documentation index at: https://mindcase.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # LinkedIn Job Search > Extract LinkedIn job details — title, company, location, URL — by specifying job titles, location, and filters `$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 **List** · Job titles to search for (e.g. 'product manager'). One per line. **Number** · Jobs to return. Use 0 for all. **List** · Filter to jobs in these locations. One per line. **List** · Filter to jobs at these companies (e.g. Google, Stripe). One per line. **Multi-select** · Filter by where the work happens. **Options:** `remote`, `hybrid`, `office` *Legend: `remote` = Remote, `hybrid` = Hybrid, `office` = On-site* **Multi-select** · Filter by employment type. **Options:** `full-time`, `part-time`, `contract`, `internship`, `temporary` *Legend: `full-time` = Full-time, `part-time` = Part-time, `contract` = Contract, `internship` = Internship, `temporary` = Temporary* **Multi-select** · Filter by required experience level. **Options:** `internship`, `entry`, `associate`, `mid-senior`, `director`, `executive` *Legend: `internship` = Internship, `entry` = Entry level, `associate` = Associate, `mid-senior` = Mid-Senior, `director` = Director, `executive` = Executive* **Multi-select** · Only jobs paying at least this much (USD). `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 →](/agents/linkedin/job-search/values#salary) **Dropdown** · Only jobs posted within this time window. **Options:** `1h`, `24h`, `week`, `month` *Legend: `1h` = Past hour, `24h` = Past 24 hours, `week` = Past week, `month` = Past month* **Dropdown** · Sort order for results. **Options:** `relevance`, `date` *Legend: `relevance` = Most relevant, `date` = Most recent* **Multi-select** · Filter by industry. [View all 434 options →](/agents/linkedin/job-search/values#industryids) **Toggle** · Only jobs you can apply to with one click on LinkedIn. **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 ```bash curl theme={null} 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" ] } }' ``` ```python Python theme={null} 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 ```json Response theme={null} { "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" } ] } ```