# Lever Jobs Scraper - Career Boards & Descriptions (`scrapingmonkey/lever-scraper`) Actor Scrape Lever company job boards with descriptions, departments, locations, apply links and published salary ranges for hiring research. Supply the employer career-board URL; collection is scoped to the selected company. - **URL**: https://apify.com/scrapingmonkey/lever-scraper.md - **Developed by:** [ScrapingMonkey](https://apify.com/scrapingmonkey) (community) - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README Collect public employer vacancies and descriptions with **Lever Scraper**. Track selected companies' openings by team, department, location and work arrangement, retaining salary ranges and application links when published. Choose the records you need and export them to CSV, JSON or Excel without supplying a site login. Use the results for company hiring intelligence. Submit matching public inputs in one run, retain the original record links, and send the structured output to your recruitment spreadsheet, reporting dashboard or research database. | At a glance | Details | |---|---| | 📥 Input | Search fields or links to the selected items; see the examples below | | 📤 Output | One row per job vacancy | | 🔐 Login required | No | | ⚡ Processing | Multiple inputs per run with automatic retries for temporary errors | | 💾 Delivery | One complete Apify dataset table; CSV, JSON and Excel export | ### What the Lever scraper collects 💼 Collect public employer vacancies and descriptions. Track selected companies' openings by team, department, location and work arrangement, retaining salary ranges and application links when published. | Collection | What you receive | |---|---| | Lever company jobs scraper | Records containing job titles, locations, published pay, descriptions, departments, ready for company hiring monitoring and career-page datasets. | Data can include: - Record identity: Record identifiers, public links and the published job title or company name. - Pay and compensation: Published salary or wage text, plus the amount, range, currency and pay-period fields supplied with the record. - Employer information: The employer board supplied for the collection. - Location and workplace: Published workplace and location information and remote or workplace-arrangement indicators. - Descriptions and requirements: Published job or company descriptions and HTML and readable text where supplied. - Employment and benefits: Employment and contract types. - Dates and hiring activity: Publication and update information. - Applications: Application destinations and instructions. ### How to scrape Lever 🚀 1. Open the Actor input form. 2. Fill in the search fields, or paste links to the items you want to collect. 3. Set the maximum results and any optional filters. 4. Start the Actor and review the collected rows. 5. Export the dataset or connect it to your application. #### Lever company jobs scraper — input example ```json { "mode": "lever-employer-jobs-scraper", "companyPages": [ "https://jobs.lever.co/zoox" ], "maxResults": 10 } ``` `maxResults: 10` means up to 10 results for **each input**. It does not guarantee that the website has that many matches. You can set the limit as low as 1. ### Lever data fields and complete output 📦 | Field group | Included data | |---|---| | Record identity | Record identifiers, public links and the published job title or company name. | | Pay and compensation | Published salary or wage text, plus the amount, range, currency and pay-period fields supplied with the record. | | Employer information | The employer board supplied for the collection. | | Location and workplace | Published workplace and location information and remote or workplace-arrangement indicators. | | Descriptions and requirements | Published job or company descriptions and HTML and readable text where supplied. | | Employment and benefits | Employment and contract types. | | Dates and hiring activity | Publication and update information. | | Applications | Application destinations and instructions. | Each collected item is a separate row. `input` identifies the submitted value and `result_type` identifies the selected mode. All returned fields appear in one table; columns that do not apply to a mode can be empty. A complete JSON result is shown for every collection mode below, in the same order as the input examples. Each example includes every field for its mode; text and lists are not shortened. Values are representative and can change. #### Lever company jobs scraper — complete JSON result ```json { "result_type": "lever-employer-jobs-scraper", "input": "https://jobs.lever.co/zoox", "status": "success", "board": "zoox", "job_id": "f4746da4-8eb8-43e2-b7ce-bf3c7cf9640d", "title": "Autonomy System Test Engineer", "url": "https://jobs.lever.co/zoox/f4746da4-8eb8-43e2-b7ce-bf3c7cf9640d", "apply_url": "https://jobs.lever.co/zoox/f4746da4-8eb8-43e2-b7ce-bf3c7cf9640d/apply", "created_at_timestamp": 1777936261125, "country": "US", "workplace_type": "hybrid", "department": "Software", "team": "Software Platforms and Product", "commitment": "Full-time", "location": "Foster City, CA", "all_locations": [ "Foster City, CA" ], "description_html": "

Description

Autonomous vehicles have some of the largest, most complex software ever shipped in a safety-critical environment. Solving that problem is one of the most exciting technical challenges of our lifetime.
\n
 
\n
As an Autonomy Systems Test Engineer at Zoox, you will help accelerate our product development by helping our developers build the safest and most reliable autonomous driving software possible. As developers build new features, you will oversee the development of extensive test plans, develop standardized simulated test design tooling processes to execute many different scenarios and put together triage pipelines for analyzing issues seen during offline and on-vehicle testing. These efforts are critical to exposing unforeseen failure modes, implementation bugs, and other issues as a result of new feature development. You will participate regularly in in-vehicle testing missions where you will see these new features behaving in the real world. Following these missions, you will help triage and root cause issues seen during testing, analyze test results to ensure existing functionality does not regress from release to release, and update our testing processes to ensure QA can continue scaling efficiently with future Zoox milestones. Your ability to distill complex systems and root cause issues will be critical to producing a safe and stable vehicle platform.
\n

In this role, you will:

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Qualifications:

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  • Bachelor’s or Master’s in Computer Science, Electrical Engineering, or related field
    • \n
  • 3+ years of experience in designing and implementing scalable software systems test strategies with excellent analytical, problem-solving, and prioritization skills
    • \n
  • Proficiency with automated test framework and test automation
    • \n
  • Experience with JIRA, GIT, Linux command line, Python, or other scripting languages
    • \n
  • Strong organizational, leadership, and communication skills
    • \n\n

     

    \n

    Bonus Qualifications:

    \n
  • Relevant industry experience in software and systems testing for robotics, autonomous mobility, or safety-critical systems.
    • \n
  • Familiarity with ISO 26262 or other safety standards
    • \n
  • Proficiency with Claude Code or other AI coding tools 
    • \n\n

    Additional information

    About Zoox
    Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

    Follow us on LinkedIn

    Accommodations
    If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

    A Final Note:
    You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
    \n

    Compensation

    Base Salary Range
    \n
     
    \n
    There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
    \n
     
    \n
    Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
    ", "description_text": "Description\nAutonomous vehicles have some of the largest, most complex software ever shipped in a safety-critical environment. Solving that problem is one of the most exciting technical challenges of our lifetime.\nAs an Autonomy Systems Test Engineer at Zoox, you will help accelerate our product development by helping our developers build the safest and most reliable autonomous driving software possible. As developers build new features, you will oversee the development of extensive test plans, develop standardized simulated test design tooling processes to execute many different scenarios and put together triage pipelines for analyzing issues seen during offline and on-vehicle testing. These efforts are critical to exposing unforeseen failure modes, implementation bugs, and other issues as a result of new feature development. You will participate regularly in in-vehicle testing missions where you will see these new features behaving in the real world. Following these missions, you will help triage and root cause issues seen during testing, analyze test results to ensure existing functionality does not regress from release to release, and update our testing processes to ensure QA can continue scaling efficiently with future Zoox milestones. Your ability to distill complex systems and root cause issues will be critical to producing a safe and stable vehicle platform.\nIn this role, you will:\nCreate test strategies and test plans for Zoox’s self-driving behavior features.\nIdentify, track, report, and resolve test strategy, planning, or implementation issues with cross-functional software development teams\nPropose, prototype, and validate a new testing methodology for driving software features using automated metrics.\nDesign, develop, and execute synthetic and log-based test scenarios on an in-house simulation test framework\nCompile triage strategy and triage results from different QA validation platforms and pipelines\nLead cross-functional QA participation in various testing pipelines, initiatives, and enablement projects.\nQualifications:\nBachelor’s or Master’s in Computer Science, Electrical Engineering, or related field\n3+ years of experience in designing and implementing scalable software systems test strategies with excellent analytical, problem-solving, and prioritization skills\nProficiency with automated test framework and test automation\nExperience with JIRA, GIT, Linux command line, Python, or other scripting languages\nStrong organizational, leadership, and communication skills\nBonus Qualifications:\nRelevant industry experience in software and systems testing for robotics, autonomous mobility, or safety-critical systems.\nFamiliarity with ISO 26262 or other safety standards\nProficiency with Claude Code or other AI coding tools\nAdditional information\nAbout Zoox\nZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.\nFollow us on LinkedIn\nAccommodations\nIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.\nA Final Note:\nYou do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.\nCompensation\nBase Salary Range\nThere are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.\nZoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.", "description_sections.heading": [ "Description", "In this role, you will: ", "Qualifications: ", "Bonus Qualifications: ", "Additional information", "Compensation" ], "description_sections.html": [ "
    Autonomous vehicles have some of the largest, most complex software ever shipped in a safety-critical environment. Solving that problem is one of the most exciting technical challenges of our lifetime.
    \n
     
    \n
    As an Autonomy Systems Test Engineer at Zoox, you will help accelerate our product development by helping our developers build the safest and most reliable autonomous driving software possible. As developers build new features, you will oversee the development of extensive test plans, develop standardized simulated test design tooling processes to execute many different scenarios and put together triage pipelines for analyzing issues seen during offline and on-vehicle testing. These efforts are critical to exposing unforeseen failure modes, implementation bugs, and other issues as a result of new feature development. You will participate regularly in in-vehicle testing missions where you will see these new features behaving in the real world. Following these missions, you will help triage and root cause issues seen during testing, analyze test results to ensure existing functionality does not regress from release to release, and update our testing processes to ensure QA can continue scaling efficiently with future Zoox milestones. Your ability to distill complex systems and root cause issues will be critical to producing a safe and stable vehicle platform.
    ", "
    \n
    ", "\n
  • Bachelor’s or Master’s in Computer Science, Electrical Engineering, or related field
    • \n
  • 3+ years of experience in designing and implementing scalable software systems test strategies with excellent analytical, problem-solving, and prioritization skills
    • \n
  • Proficiency with automated test framework and test automation
    • \n
  • Experience with JIRA, GIT, Linux command line, Python, or other scripting languages
    • \n
  • Strong organizational, leadership, and communication skills
    • \n\n

     

    ", "\n
  • Relevant industry experience in software and systems testing for robotics, autonomous mobility, or safety-critical systems.
    • \n
  • Familiarity with ISO 26262 or other safety standards
    • \n
  • Proficiency with Claude Code or other AI coding tools 
    • \n", "
    About Zoox
    Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.

    Follow us on LinkedIn

    Accommodations
    If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

    A Final Note:
    You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
    ", "
    Base Salary Range
    \n
     
    \n
    There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
    \n
     
    \n
    Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
    " ], "description_sections.text": [ "Autonomous vehicles have some of the largest, most complex software ever shipped in a safety-critical environment. Solving that problem is one of the most exciting technical challenges of our lifetime.\nAs an Autonomy Systems Test Engineer at Zoox, you will help accelerate our product development by helping our developers build the safest and most reliable autonomous driving software possible. As developers build new features, you will oversee the development of extensive test plans, develop standardized simulated test design tooling processes to execute many different scenarios and put together triage pipelines for analyzing issues seen during offline and on-vehicle testing. These efforts are critical to exposing unforeseen failure modes, implementation bugs, and other issues as a result of new feature development. You will participate regularly in in-vehicle testing missions where you will see these new features behaving in the real world. Following these missions, you will help triage and root cause issues seen during testing, analyze test results to ensure existing functionality does not regress from release to release, and update our testing processes to ensure QA can continue scaling efficiently with future Zoox milestones. Your ability to distill complex systems and root cause issues will be critical to producing a safe and stable vehicle platform.", "Create test strategies and test plans for Zoox’s self-driving behavior features.\nIdentify, track, report, and resolve test strategy, planning, or implementation issues with cross-functional software development teams\nPropose, prototype, and validate a new testing methodology for driving software features using automated metrics.\nDesign, develop, and execute synthetic and log-based test scenarios on an in-house simulation test framework\nCompile triage strategy and triage results from different QA validation platforms and pipelines\nLead cross-functional QA participation in various testing pipelines, initiatives, and enablement projects.", "Bachelor’s or Master’s in Computer Science, Electrical Engineering, or related field\n3+ years of experience in designing and implementing scalable software systems test strategies with excellent analytical, problem-solving, and prioritization skills\nProficiency with automated test framework and test automation\nExperience with JIRA, GIT, Linux command line, Python, or other scripting languages\nStrong organizational, leadership, and communication skills", "Relevant industry experience in software and systems testing for robotics, autonomous mobility, or safety-critical systems.\nFamiliarity with ISO 26262 or other safety standards\nProficiency with Claude Code or other AI coding tools", "About Zoox\nZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.\nFollow us on LinkedIn\nAccommodations\nIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.\nA Final Note:\nYou do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.", "Base Salary Range\nThere are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.\nZoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance." ], "salary_range.currency": "USD", "salary_range.interval": "per-year-salary", "salary_range.minimum": 144000, "salary_range.maximum": 193000, "salary_description_html": "
    Base Salary Range
    \n
     
    \n
    There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
    \n
     
    \n
    Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
    ", "native_limit_reached": false } ``` Images, tags and other lists stay with their parent result instead of creating extra rows. Invalid or unavailable inputs, inputs with no results, and requests that fail after all retries produce a row with `status: failed`. At most one failed row is saved per input; it includes `error_code` and `error_message` explaining the outcome. A normal end of pagination after collected results does not add a failed row. ### Input requirements and collection settings ⚙️ | Setting | What to enter | |---|---| | **Maximum results per search or link** (`maxResults`) | Collect up to this many results for each search or link. Minimum: 1. | | **Company careers pages** (`companyPages`) | Paste the company careers page on this service. One company per line. | | Collection mode | Fields to use | |---|---| | Employer Jobs | **Company careers pages** | The result limit applies separately to each search or supplied link. Collection ends earlier when no more matching results are available. ### Lever scraping use cases 🎯 #### Hiring activity monitoring Run repeat collections of selected employer career pages and compare vacancy titles and original links over time to identify newly advertised roles and changes in hiring activity. #### Advertised compensation research Compare the compensation published in Lever records. Keep the original salary text, units and available pay-period context when preparing recruitment or labour-market reports. #### Working-condition comparison Compare the contract, schedule or benefit information published in Lever records when researching how employers present their opportunities. #### Location-based market mapping Group the returned Lever records by their published location or workplace information to study where employers advertise opportunities and concentrate recruitment activity. #### Recruitment data products Use the exported public employer vacancies and descriptions as input to spreadsheets, recruitment dashboards or employer research databases, preserving original links so analysts can review the source. ### Pricing and saved-result behavior 💰 See the Actor's **Pricing** tab for the active pricing model and current rate. Store settings may change, so this README does not claim a fixed cost. Under dataset-item pricing: - Each collected item saved in the dataset is one result. - Images, tags and other values attached to that item do not create additional rows. - Automatic retry attempts do not create extra dataset rows. - A saved `failed` row is also one billable dataset item, including invalid inputs, unavailable items, no results, or exhausted retries. At most one failed row is saved per input, including when some results were already collected. - `maxResults` caps all saved rows for each input, including its failed row. Repeated copies of the same input are processed once. More inputs or a higher limit can produce more saved results. ### Lever scraper API and integrations 🔌 Replace `$ACTOR_ID` with the ID shown in the Actor API tab and `$APIFY_TOKEN` with your token. ```bash curl -X POST "https://api.apify.com/v2/acts/$ACTOR_ID/runs?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"mode":"lever-employer-jobs-scraper","companyPages":["https://jobs.lever.co/zoox"],"maxResults":10}' ``` Use schedules for recurring collection, webhooks for completion notifications, and Apify integrations for Google Sheets, Make, Zapier, cloud storage, a CRM or your own application. ### Reliability, retries, and public-data limits ⚠️ Temporary connection errors, timeouts and access restrictions are retried automatically, up to five attempts. Invalid inputs save a failed row without an HTTP request; confirmed unavailable items save a failed row without unnecessary retries. Exhausted retries also save a failed row. Results already collected remain available if a later request fails, and normal pagination completion adds no error row. Collection also stops after two consecutive fully processed pages add no new results, even if the website provides another cursor. Required detail lookups are completed before checking a page; new results reset the counter, and independent reply branches are checked separately. Failures while initializing the Actor, saving data or scheduling requests stop the run instead of being reported as a failed website result. Inputs identify an employer's Lever board. There is no global employer discovery; an unusually large board can reach the source's own result limit. Lever controls which information is publicly available. Removed, private or restricted items may be unavailable, and optional values can be null or empty. A run can still fail if the results cannot be saved. ### Frequently asked questions ❓ #### Does it require an account on Lever? No. You do not need to provide an account, password or login cookies. Only publicly available information is collected. #### How does maxResults work? It limits the number of saved results separately for every input. The minimum is 1. With maxResults set to 10, each input returns at most 10 available results. #### Does it search every Lever employer? No. Each input identifies one public employer board. Supply the boards you want to monitor. #### Are descriptions and salary information included? Job descriptions and published salary ranges are included when the board supplies them. A salary field can be empty if the employer does not disclose compensation. #### Why are some fields empty? The website may not publish that value, or the field may belong to a different collection mode. Missing values remain null or empty instead of being guessed. #### Can I export the results to a spreadsheet? Yes. Download CSV, Excel or JSON from the Apify dataset. All returned fields are included in the same results table. ### Support and responsible use 🛟 For a reproducible issue, share the run ID, selected mode, result limit and a safe public example through the support channel. Never disclose access tokens, passwords or proxy credentials. Use public Lever information lawfully and responsibly. Follow applicable privacy, copyright, data-protection, contractual and platform requirements when storing, analyzing or redistributing results. # Actor input Schema ## `mode` (type: `string`): Choose the information to collect. ## `maxResults` (type: `integer`): Collect up to this many results for each search or link. Minimum: 1. ## `companyPages` (type: `array`): Paste the company careers page on this service. One company per line. ## Actor input object example ```json { "mode": "lever-employer-jobs-scraper", "maxResults": 10, "companyPages": [ "https://jobs.lever.co/zoox" ] } ``` # Actor output Schema ## `results` (type: `string`): Collected entities and failed input outcomes, with all available fields and error explanations in one dataset. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "mode": "lever-employer-jobs-scraper", "maxResults": 10, "companyPages": [ "https://jobs.lever.co/zoox" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapingmonkey/lever-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "mode": "lever-employer-jobs-scraper", "maxResults": 10, "companyPages": ["https://jobs.lever.co/zoox"], } # Run the Actor and wait for it to finish run = client.actor("scrapingmonkey/lever-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "mode": "lever-employer-jobs-scraper", "maxResults": 10, "companyPages": [ "https://jobs.lever.co/zoox" ] }' | apify call scrapingmonkey/lever-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapingmonkey/lever-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/vLIVDiRyw3OiT6cOp/builds/qI9FkqF2Nk07GDenB/openapi.json