# Lever Jobs Scraper: Job Board with Salary Ranges (`mrslm_data/lever-jobs`) Actor

Lever jobs scraper with salary ranges: min, max, currency and pay period when posted, plus team, location, remote/hybrid, apply link. Any jobs.lever.co board.

- **URL**: https://apify.com/mrslm_data/lever-jobs.md
- **Developed by:** [MRSLM Data](https://apify.com/mrslm_data) (community)
- **Categories:** Jobs
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.80 / 1,000 jobs

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

## Lever Jobs Scraper: Job Board with Salary Ranges

**Open roles from any company's Lever job board: team, location, remote/hybrid, commitment, salary range when posted, links and full description. $1.00 per 1,000 jobs.**

This Lever jobs scraper reads the public `jobs.lever.co/<company>` board (and the EU `jobs.eu.lever.co` boards), so you get every open role without an API key or login, with the salary range split into min, max, currency and pay period whenever the company posts one.

Lever boards are where many US and European scale-ups publish salary ranges, so you can track pay bands as well as headcount.

### Quick start

1. Press **Start**. The form is already filled with this example input, so the first run returns real rows in under a minute:

```json
{
  "companies": [
    "palantir",
    "https://jobs.lever.co/spotify"
  ],
  "maxJobsPerCompany": 10
}
```

2. Swap in your own values, or call the Actor through the Apify API, Make, Zapier, n8n or the Python/JS clients with the same JSON.
3. Download the results as JSON, CSV or Excel from the **Output** tab, or schedule the run to repeat.

**Full guide: How to Scrape Lever Job Postings with Salary Ranges (Real Run on 3 Companies)**

### What the Lever Jobs Scraper does

You give the Actor a list of Lever boards as names (`shieldai`) or links (`jobs.lever.co/shieldai`, including EU boards on `jobs.eu.lever.co`). It reads each board's public postings feed, applies your filters, sorts by posting date and saves one row per job.

Lever's feed is one of the richest public job feeds: it carries a workplace type (remote, hybrid or on-site), a commitment such as full-time or intern, the team and department, the country and, when the company fills it in, a salary range with currency and pay period. The Actor maps all of it into tidy columns. You only pay for jobs saved after your filters.

- Structured `salary` object: `min`, `max`, `currency`, `period` (such as `per-year-salary` or `per-hour-wage`) and any free-text note.
- Filters by title words, excluded title words, location, department or team, remote and posting date.
- Same columns as our Greenhouse, Workable and multi-ATS scrapers, so you can combine the files.

### Who it is for

- **Compensation analysts and HR teams**: benchmark posted pay ranges for a role family across competitors, by city and currency.
- **Recruiters**: see which target companies are hiring, for what, and at what published pay, before you reach out.
- **Sales teams**: use new roles in a buyer department as a timely trigger for outreach.
- **Job seekers**: track the companies you like and sort the roles by the top of the published range.
- **Researchers and journalists**: study pay transparency in practice: who publishes ranges, and how wide they are.

### Real example: engineering pay ranges at Shield AI, Outreach and PointClickCare

Say you are benchmarking engineering pay. You pick three Lever companies that publish ranges: Shield AI (autonomy software and aircraft, US), Outreach (sales software, US and India) and PointClickCare (healthcare software, Canada and the US). You want up to six of the newest engineering roles from each.

#### Step 1: Enter the input

Open the [Lever Jobs Scraper](https://apify.com/mrslm_data/lever-jobs) in Apify Console, switch the input form to **JSON** and paste this. It is the exact input used for the run in this guide:

```json
{
  "companies": [
    "shieldai",
    "outreach",
    "pointclickcare"
  ],
  "titleKeywords": [
    "engineer"
  ],
  "maxJobsPerCompany": 6
}
```

What each setting does:

- `companies`: Lever board names, as they appear in `jobs.lever.co/<name>`. Links work too.
- `titleKeywords`: keep jobs whose title contains any of these words, ignoring case.
- `maxJobsPerCompany`: save at most six jobs per company, the newest first because `newestFirst` defaults to true.

#### Step 2: Run it

Press **Start**. On 30 October 2026 this input finished with status `SUCCEEDED` in about 6 seconds and saved 16 rows to the run's dataset. The run was charged 16 `job` events plus one start event, so the bill was $0.0161 on the Free/Bronze tier. Per the run summary, Shield AI had 655 open jobs and 434 had "engineer" in the title, so the 6 newest were saved. PointClickCare had 72 open, 22 matched and 6 were saved. Outreach had 19 open and 4 matched, so all 4 were saved.

#### Step 3: Read the output

Here are the first rows of the real dataset, cut to the most useful columns:

| company | title | location | workplaceType | salary | postedAt |
|---|---|---|---|---|---|
| outreach | Staff Software Engineer (Backend Engineer – Gola… | Hyderabad | remote |  | 2026-10-21T11:34:17.428Z |
| outreach | Staff Software Engineer (Backend) | Hyderabad | remote |  | 2026-10-19T10:26:32.590Z |
| outreach | Senior Forward Deployed Engineer, Managed Servic… | Hyderabad | remote |  | 2026-10-08T09:39:35.755Z |
| outreach | Staff Software Engineer, Identity and Access Pla… | Seattle, WA | hybrid | {"min": 165000, "max": 215000, "currency": "USD"… | 2024-09-24T18:33:25.687Z |
| pointclickcare | Intermediate Software Engineer | Mississauga/Toronto/Kitchener/Waterloo/Cambridge | hybrid | {"min": 112000, "max": 125000, "currency": "CAD"… | 2026-10-21T20:57:35.853Z |
| pointclickcare | Intermediate Site Reliability Engineer (SRE) | Salt Lake City, UT | hybrid | {"min": 138000, "max": 154000, "currency": "USD"… | 2026-10-19T20:42:32.137Z |
| pointclickcare | Intermediate Software Engineer-(A\&P) | Salt Lake City, UT | hybrid | {"min": 123000, "max": 137000, "currency": "USD"… | 2026-10-09T20:31:23.642Z |
| pointclickcare | Marketing Data Analytics Engineer (CA) | Remote or Mississauga | remote | {"min": 82000, "max": 92000, "currency": "CAD",… | 2026-10-09T14:40:06.079Z |
| pointclickcare | Marketing Data Analytics Engineer (US) | Remote, USA | remote | {"min": 87000, "max": 97000, "currency": "USD",… | 2026-10-09T14:38:40.559Z |
| pointclickcare | Senior Machine Learning Systems Engineer (CAD) | Mississauga | hybrid | {"min": 174000, "max": 218000, "currency": "CAD"… | 2026-09-22T12:55:14.879Z |
| shieldai | Senior Applications Engineer, Maritime Autonomy… | United States | on-site | {"min": 130000, "max": 200000, "currency": "USD"… | 2026-10-30T08:39:52.314Z |
| shieldai | Summer 2027 - Product Support Engineering Intern… | Dallas, Texas | on-site | {"min": 37, "max": 97, "currency": "USD", "perio… | 2026-10-28T22:25:02.681Z |
| shieldai | Senior Software Engineer, Frontend Platform (R57… | San Diego, California | on-site | {"min": 130000, "max": 240000, "currency": "USD"… | 2026-10-28T20:13:16.822Z |
| shieldai | Senior Field Services Engineer (R6380) | San Diego, California | on-site | {"min": 84000, "max": 127000, "currency": "USD",… | 2026-10-27T22:38:21.899Z |
| shieldai | Staff Engineer, Propulsion (R5899) | Dallas, Texas | on-site | {"min": 146000, "max": 219000, "currency": "USD"… | 2026-10-27T16:45:38.741Z |
| shieldai | Engineer II, Autonomy (R5714) | Taipei | hybrid |  | 2026-10-26T04:54:38.600Z |

And one full row as JSON (long text shortened with …):

```json
{
  "platform": "Lever",
  "company": "shieldai",
  "jobId": "f8b2ffef-ae89-4860-ba6f-b5e59cb6d31e",
  "title": "Senior Software Engineer, Frontend Platform (R5790)",
  "department": "Hivemind Enterprise Division",
  "team": "Engineering",
  "location": "San Diego, California",
  "country": "US",
  "workplaceType": "on-site",
  "isRemote": false,
  "employmentType": "full-time-employee",
  "salary": {
    "min": 130000,
    "max": 240000,
    "currency": "USD",
    "period": "per-year-salary",
    "text": null
  },
  "postedAt": "2026-10-28T20:13:16.822Z",
  "url": "https://jobs.lever.co/shieldai/f8b2ffef-ae89-4860-ba6f-b5e59cb6d31e",
  "applyUrl": "https://jobs.lever.co/shieldai/f8b2ffef-ae89-4860-ba6f-b5e59cb6d31e/apply"
}
```

What the 16 real rows show:

- **Pay ranges are common, and wide.** 14 of 16 rows have a `salary` object. Shield AI's Senior Software Engineer, Frontend Platform in San Diego is posted at $130,000 to $240,000 a year. Its Staff Engineer, Propulsion in Dallas is $146,000 to $219,000. A range that wide usually spans several levels, so compare midpoints rather than minimums.
- **Currency and period are real columns.** PointClickCare posts its Canadian roles in CAD (Intermediate Software Engineer: CAD 112,000 to 125,000) and its Salt Lake City roles in USD (Intermediate SRE: USD 138,000 to 154,000). Shield AI's Summer 2027 product support engineering intern is `per-hour-wage`, $37 to $97. Never average those together without converting the currency and the period first.
- **Missing ranges are honest gaps.** Outreach's three newest roles are in Hyderabad and carry no range, and Shield AI's Engineer II in Taipei has none either. Pay-transparency rules are mostly a US and Canadian thing, so non-US roles often have no range.
- **Old postings stay open.** Outreach's Staff Software Engineer, Identity and Access Platform was posted on 24 September 2024 and is still live. Use `postedWithinDays` if you only want fresh roles.
- **Workplace type is structured.** Lever gives `remote`, `hybrid` or `on-site` directly, so Shield AI shows as on-site and PointClickCare as mostly hybrid without any text parsing.

Lever's `employmentType` values are whatever the company uses: Shield AI says `full-time-employee`, `intern` and `international-eor`, the others say `full-time`. Normalise them if you group by type.

### Is there a Lever jobs API?

Yes. Lever publishes every company's open postings at a public endpoint, with no key needed:

```
GET https://api.lever.co/v0/postings/{company}?mode=json
```

EU-hosted boards use `api.eu.lever.co`. The Actor reads this feed, converts epoch-millisecond dates to ISO dates, flattens categories into department, team, location and commitment, turns `salaryRange` into the `salary` object, and adds your filters, sorting and run summary. Lever's other API, the one with candidates and opportunities, is private to each company and is never touched.

Not every Lever company fills in `salaryRange`. In our probing, Palantir and Spotify did not, while Shield AI, Outreach, PointClickCare, Match Group, Aledade and Tala did. If pay is the point of your project, check a few companies first with a small `maxJobsPerCompany`.

### Output fields

Each row in the dataset has these fields. The example column shows a value from the run above.

| Field | What it means | Example from this run |
|---|---|---|
| `platform` | The ATS the job came from, e.g. Greenhouse, Lever or Workable. | Lever |
| `company` | The board name you gave, or the one the Actor detected. | outreach |
| `companyName` | The company display name, when the board publishes it. | outreach |
| `jobId` | The ATS job ID. Stable from run to run, so use it to spot new jobs. | 88257b0f-9915-4e5f-96bf-d37b183b6cf6 |
| `title` | The job title as posted. | Staff Software Engineer (Backend Engineer – Golang / 7+ Year… |
| `department / team` | Department and team, when the company sets them. | Engineering / Engineering |
| `location / locations` | The main location text, plus every location for multi-office roles. | Hyderabad / Hyderabad |
| `country` | Country, when the platform gives one. | IN |
| `workplaceType / isRemote` | remote, hybrid or on-site, plus a true/false remote flag. | remote / yes |
| `employmentType` | full-time, part-time, intern and so on, when published. | full-time |
| `seniority` | Experience level, when the platform publishes one. | (empty in this run) |
| `salary` | Structured pay range (min, max, currency, period, text) when the company publishes it; otherwise empty. | {"min": 165000, "max": 215000, "currency": "USD", "period":… |
| `postedAt / updatedAt` | When the job was first published and last edited (ISO dates). | 2026-10-21T11:34:17.428Z / (empty in this run) |
| `url / applyUrl` | The public job page and the application page. | https://jobs.lever.co/outreach/88257b0f-9915-4e5f-96bf-d37b1… / https://jobs.lever.co/outreach/88257b0f-9915-4e5f-96bf-d37b1… |
| `boardUrl` | The company's careers board. | https://jobs.lever.co/outreach |
| `scrapedAt` | When the row was read (UTC). | 2026-10-30T16:15:08.248Z |

In CSV and Excel exports the salary object becomes `salary/min`, `salary/max`, `salary/currency` and `salary/period` columns, ready to sort. In the export URL, ask for `fields=salary` and you get all of those sub-columns; a path such as `salary/min` in `fields` comes back empty.

### Export Lever jobs to CSV, Excel or Google Sheets

Every run saves its rows to a dataset, and a dataset can be downloaded in any common format. You do not need to write code for this.

**From Apify Console.** Open the run, go to the **Output** tab and click **Export**. Pick CSV, Excel (XLSX), JSON, XML, HTML or RSS. You can tick only the columns you want, for example `company`, `title`, `location`, `salary`, `postedAt`. Nested values such as lists are flattened into columns like `salary/min` in CSV and Excel.

**From a URL.** The same export is a plain HTTPS link. Replace `<DATASET_ID>` with the dataset ID shown on the run's Storage tab:

```bash
## CSV with just the columns you need
curl -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://api.apify.com/v2/datasets/<DATASET_ID>/items?format=csv&clean=1&fields=company,title,location,salary,postedAt,url" -o lever-jobs.csv

## Excel
curl -H "Authorization: Bearer $APIFY_TOKEN" \
  "https://api.apify.com/v2/datasets/<DATASET_ID>/items?format=xlsx&clean=1" -o lever-jobs.xlsx
```

**Into Google Sheets.** You have three good options:

1. **One-off:** download the CSV and use **File > Import > Upload** in Google Sheets. Choose "Replace current sheet" to refresh an existing tab.
2. **Automatic, no code:** in Make, Zapier or n8n, use the Apify app's "Watch Actor runs" (or "Run Actor") trigger, then "Get dataset items", then the Google Sheets "Add row" action. Every scheduled run then lands in your sheet. Apify's own [Google Sheets Import & Export](https://apify.com/lukaskrivka/google-sheets) Actor can also append a dataset to a sheet, and you can chain it to this Actor's runs with an integration.
3. **Formula:** `=IMPORTDATA("https://api.apify.com/v2/actor-tasks/<USERNAME>~<TASK_NAME>/runs/last/dataset/items?status=SUCCEEDED&format=csv&token=<YOUR_TOKEN>")` always pulls the latest successful run of a saved task. The token sits in the formula, so anyone who can open the sheet can see it. Only use this in a private sheet.

### Schedule it to run every Monday at 6:00

Job boards change every day. A daily run with `postedWithinDays` set to 1 or 2 gives you only the new roles, which keeps each run small and cheap. Because `jobId` is stable, you can also keep the full list and compare it with yesterday's to see which roles closed.

For pay benchmarking, a weekly run is usually enough. Keep each week's file and you can see when a company widens or raises a published range.

1. In the Actor's input form, set up the input from Step 1 and click **Save as new task**. Give it a clear name such as `lever-pay-benchmark`.
2. Go to **Schedules > Create new**, set the cron expression to `0 6 * * 1` and pick your timezone, so it runs every Monday at 6:00.
3. Add the task to the schedule and save. Each run gets its own fresh dataset.
4. Optional: on the task's **Integrations** tab, add a webhook, Slack or email notification for "Run succeeded", or connect Make, Zapier or n8n, so the new rows go where you need them.

To fetch the newest results without looking up a run ID, use the task's last-run link: `https://api.apify.com/v2/actor-tasks/<USERNAME>~lever-pay-benchmark/runs/last/dataset/items?status=SUCCEEDED&format=json`.

### Call it from the API (Python, JavaScript or curl)

You can start the Actor from your own code with the official Apify clients. Put your API token (Console > Settings > API & Integrations) in an environment variable called `APIFY_TOKEN` rather than in the code.

**Python** (`pip install "apify-client>=3"`). Tested with apify-client 3.4:

```python
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run_input = {
    "companies": [
        "shieldai",
        "outreach",
        "pointclickcare"
    ],
    "titleKeywords": [
        "engineer"
    ],
    "maxJobsPerCompany": 6
}

run = client.actor("mrslm_data/lever-jobs").call(run_input=run_input)

## apify-client 3.x returns a Run object, so use run.default_dataset_id
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item["title"], item["salary"])
```

In apify-client 3.x, `call()` returns a typed object. Older examples that use `run["defaultDatasetId"]` were written for 1.x and 2.x and fail in 3.x with `TypeError: 'Run' object is not subscriptable`.

**JavaScript / Node.js** (`npm install apify-client`):

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const input = {
    "companies": [
        "shieldai",
        "outreach",
        "pointclickcare"
    ],
    "titleKeywords": [
        "engineer"
    ],
    "maxJobsPerCompany": 6
};

const run = await client.actor('mrslm_data/lever-jobs').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, items[0]);
```

**curl**, one request that runs the Actor and returns the rows as CSV (it waits up to 5 minutes, so keep the input small):

```bash
curl -X POST "https://api.apify.com/v2/acts/mrslm_data~lever-jobs/run-sync-get-dataset-items?format=csv" \
  -H "Authorization: Bearer $APIFY_TOKEN" -H "Content-Type: application/json" \
  -d '{"companies": ["shieldai", "outreach", "pointclickcare"], "titleKeywords": ["engineer"], "maxJobsPerCompany": 6}' -o lever-jobs.csv
```

### What it costs

The Actor uses pay-per-event pricing. **Job**: $1.00 per 1,000 on the Free and Bronze tiers, $0.90 on Silver and $0.80 on Gold. Each run also has a start fee of $0.00005 per GB of memory (one event at the default memory). You are not billed separately for compute on normal runs: the event prices are the whole bill.

#### Price per event

Current pay-per-event prices for this Actor on Apify, by Apify subscription plan:

| Event (per 1,000) | Free / Bronze | Silver | Gold / Platinum / Diamond |
|---|---|---|---|
| Job (`job`) | $1.00 | $0.90 | $0.80 |
| Actor start (once per run at the default memory, not per 1,000) | $0.00005 | $0.00005 | $0.00005 |

You are charged only for the events in this table: nothing for compute, and nothing for searches that return no rows beyond the start fee.

| Scenario | Free / Bronze | Silver | Gold |
|---|---|---|---|
| The run in this guide (16 jobs) | $0.0161 | $0.0144 | $0.0129 |
| Full export of Shield AI's 655 open roles | $0.66 | $0.59 | $0.52 |
| Weekly pay benchmark: 50 companies, about 400 matching roles each week (4 runs a month) | $1.60 | $1.44 | $1.28 |
| Daily new-roles feed of about 50 jobs, for a year (365 runs) | $18.27 | $16.44 | $14.62 |

To cap spending, set **Maximum cost per run** in the run options (or `maxTotalChargeUsd` in the API). The Actor stops cleanly at the cap and you are never billed past it.

### Limits

- It reads open jobs only. Closed roles are gone from the public board, so keep your own history if you need it.
- Filters are plain keyword matches on the title, location or department text. `engineer` also matches "Engineering Manager" and "Solutions Engineer"; use `excludeTitleKeywords` to trim.
- Descriptions are capped at 5,000 characters of plain text when `includeDescription` is on.
- Salary only when the company publishes `salaryRange` on Lever. The Actor does not guess pay from the description.
- Lever boards only. For a mixed list of Lever, Greenhouse, Workable and other ATS, use the [ATS Jobs Scraper](https://apify.com/mrslm_data/ats-jobs).
- Values such as `employmentType` and `department` are the company's own labels and are not normalised across companies.

### FAQ

**What share of Lever jobs list a salary?** It depends on the company and on local pay-transparency rules. The Actor never guesses: when a posting has no range, the salary fields are `null`.

**Does every Lever posting have a salary?**
No. Only postings where the company filled in the pay range. In this run 14 of 16 did; at Palantir and Spotify, none did.

**What do the salary period values mean?**
They come from Lever: `per-year-salary`, `per-month-salary`, `per-hour-wage` and so on. Convert to one period before comparing.

**Does it work with EU Lever boards?**
Yes. Pass the `jobs.eu.lever.co/<name>` link and the Actor reads the EU API.

**Do I need an API key or a login for the job board?**
No. Every board this Actor reads is the public one behind the company's careers page. You only need your own Apify token to run the Actor.

**Does it include recruiter or applicant data?**
No. Only the public job ad. Application questions, recruiters and candidates are never read, and email addresses and phone numbers in descriptions are removed.

**How fresh is the data?**
Live. Each run reads the boards at that moment, so closed jobs disappear and new ones appear.

**What happens if I mistype a company name?**
That company is reported as not found in the run summary and costs nothing. The rest of the run carries on.

**How do I get only new jobs every day?**
Save your input as a task with `postedWithinDays` set to 1 and give it a daily schedule. For boards with irregular dates, set it to 2 and drop duplicates by `jobId`.

**Can I run it on a schedule?**
Yes. Save your input as a task and attach a schedule, as shown above. Each run is independent and returns the Lever jobs available at that moment.

**Does it work with Make, Zapier or n8n?**
Yes. All three have an Apify app. Use "Run Actor" (or run a saved task), then "Get dataset items" to pass the rows to the next step, such as Google Sheets, Airtable, a CRM or Slack.

**Can AI agents use it through MCP?**
Yes. Apify's hosted MCP server can expose this Actor as a tool to any MCP client (Claude Desktop, Cursor, VS Code and others). Add `https://mcp.apify.com/?tools=mrslm_data/lever-jobs` as a remote MCP server and sign in with your Apify account or API token. The agent fills in the same input fields shown above and gets the same rows back, billed at the same per-event prices.

### Is it legal?

This Actor only reads pages and feeds that the website itself publishes to every visitor without a login. It obeys each site's robots.txt, keeps a polite request rate, and never tries to get past logins, paywalls, captchas or bot checks. It does not collect personal data such as emails, phone numbers or names of private individuals. You are responsible for how you use the data: follow the source site's terms, copyright and the privacy laws that apply to you (GDPR, CCPA, etc.). This tool is independent and not affiliated with or endorsed by the platforms it reads.

# Actor input Schema

## `companies` (type: `array`):

Lever board URLs or names. One per line.

## `titleKeywords` (type: `array`):

Keep jobs whose title contains any of these words (e.g. engineer, sales). Empty = all jobs.

## `excludeTitleKeywords` (type: `array`):

Drop jobs whose title contains any of these words (e.g. intern).

## `locationKeywords` (type: `array`):

Keep jobs whose location or country contains any of these (e.g. London, Germany, remote).

## `departmentKeywords` (type: `array`):

Keep jobs whose department or team contains any of these (e.g. engineering).

## `remoteOnly` (type: `boolean`):

Keep only jobs marked remote.

## `postedWithinDays` (type: `integer`):

Keep only jobs posted in the last N days. 0 = any date.

## `includeDescription` (type: `boolean`):

Add the full job description as plain text (up to 5,000 characters). Makes rows larger.

## `newestFirst` (type: `boolean`):

Sort each company's jobs by posting date, newest first (so per-company limits keep the newest).

## `maxJobsPerCompany` (type: `integer`):

0 = all open jobs.

## `maxResults` (type: `integer`):

Safety cap on saved jobs across the whole run. 0 = no cap. Your max cost per run is always respected.

## `proxyConfiguration` (type: `object`):

Usually not needed.

## Actor input object example

```json
{
  "companies": [
    "palantir",
    "https://jobs.lever.co/spotify"
  ],
  "remoteOnly": false,
  "postedWithinDays": 0,
  "includeDescription": false,
  "newestFirst": true,
  "maxJobsPerCompany": 10,
  "maxResults": 0,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `results` (type: `string`):

All jobs as a dataset (JSON, CSV, Excel and more via the API or Console).

## `summary` (type: `string`):

Jobs per board, boards that failed, and the stop reason.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "companies": [
        "palantir",
        "https://jobs.lever.co/spotify"
    ],
    "maxJobsPerCompany": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("mrslm_data/lever-jobs").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "companies": [
        "palantir",
        "https://jobs.lever.co/spotify",
    ],
    "maxJobsPerCompany": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("mrslm_data/lever-jobs").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 '{
  "companies": [
    "palantir",
    "https://jobs.lever.co/spotify"
  ],
  "maxJobsPerCompany": 10
}' |
apify call mrslm_data/lever-jobs --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,mrslm_data/lever-jobs"
        }
    }
}
```

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 <APIFY_API_TOKEN>` 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/Q8vmR9wxqRg5Yww8e/builds/ycmF7BK3m5063p5gu/openapi.json