# Levels.fyi Salary Scraper: Pay by Level & Percentiles (`tacps126/levels-fyi-salaries`) Actor

Levels.fyi compensation: total, base, stock and bonus for every level at any company and job family, in any city or country, with p10-p90 percentiles, years of experience, median offer, top-paying companies and locations, and company profiles.

- **URL**: https://apify.com/tacps126/levels-fyi-salaries.md
- **Developed by:** [Tapaswai Choudhary](https://apify.com/tacps126) (community)
- **Categories:** Jobs, Business, Automation
- **Security:** Limited permissions
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $8.00 / 1,000 rows

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
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

## Levels.fyi Salary Scraper: Pay by Level & Percentiles

Compensation from **Levels.fyi** for any company, job family and location: **total, base, stock and bonus for every level** (L3, L4, Senior, Staff...), with submissions, years of experience, p10-p90 percentiles, the median offer and the company's profile. Or pull a job family's whole market (top-paying companies and locations) or a company's pay across all its job families.

**Built for** recruiters and talent teams setting pay bands, compensation analysts, job seekers preparing to negotiate, HR-tech and salary tools, and AI agents.

### What you get

**Pay by level** (one row per level):

| Field | Meaning |
|---|---|
| `company`, `jobFamily`, `location`, `level`, `levelTitles`, `levelDescription` | Who, what role, where, which level and its other names |
| `totalCompensation`, `baseSalary`, `stockPerYear`, `bonus`, `commission` | Average yearly pay in USD |
| `localCurrency`, `exchangeRate`, `localTotalCompensation` | The same in the location's currency |
| `submissions`, `submissionsLast12Months`, `sampleTotals` | How much data backs it, and individual totals |
| `yearsOfExperienceAverage`, `yearsOfExperienceMedian`, `typicalYearsOfExperience` | Experience at that level |
| `percentWorkforce` | Share of the company's workforce at that level, where published |
| `jobFamilyPercentiles` | p10-p90 of total, base, stock and bonus for the job family |
| `medianOffer` | The median submission: level, focus, experience, location, pay split |
| `otherTitles` | Other titles at the company in that job family, with their pay |
| `companyProfile` | Website, LinkedIn, careers page, HQ, employees, ticker, vesting schedule, aliases |

**Market** (one row per job family and location): submissions, p10-p90 percentiles for total, base, stock and bonus, histogram, top-paying companies, top-paying locations and titles.

**Company overview** (one row per job family at the company): median total pay, submissions, titles, the company's overall median and its lowest- and highest-paying job families.

### Why this Actor

- **Every location.** Countries and city areas (India, United Kingdom, New York City Area, Bangalore...), with pay in local currency.
- **More than the level averages.** Percentiles, median offer, typical experience, workforce share, other titles and the company profile in every row, at no extra charge.
- **Three views** of the same data: by level, by market, by company.
- **AI insights (optional).** Where each level's pay sits, a negotiation tip and how much data backs it; with your profile, a fit score.
- **For AI agents.** Callable as an MCP tool.

### How to use it

Pay by level at three companies, in the US and India:

```json
{
  "companies": ["google", "meta", "microsoft"],
  "jobFamilies": ["software-engineer"],
  "locations": ["united-states", "india"]
}
```

Top-paying companies for product managers in the UK:

```json
{ "mode": "market", "jobFamilies": ["product-manager"], "locations": ["united-kingdom"] }
```

Every job family at a company:

```json
{ "mode": "company", "companies": ["stripe", "openai"] }
```

### Pricing

**$10 per 1,000 rows** plus a start fee per run. AI insights, when you turn them on, are $0.01 each, plus the model's tokens: about $0.0003 per insight with the default model (billed to your Apify account by Apify's AI gateway), or your provider's price with your own key. On the Apify free plan a run returns up to 100 rows.

### Good to know

- Figures are the averages and percentiles Levels.fyi publishes on its public pages; individual submissions behind its sign-in are not included.
- Slugs are as in Levels.fyi links: `software-engineer`, `product-manager`, `data-scientist`, `software-engineering-manager`; companies by name or slug.
- Need another view or field? **Contact tacps126@gmail.com**.

# Actor input Schema

## `mode` (type: `string`):

Pay by level: one row per level (L3, L4...) for each company and job family. Market: one row per job family and location. Company overview: one row per job family at each company.

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

Company names or Levels.fyi slugs, e.g. google, meta, jpmorgan-chase.

## `jobFamilies` (type: `array`):

e.g. software-engineer, product-manager, data-scientist, software-engineering-manager. Empty = software-engineer.

## `locations` (type: `array`):

Optional city areas or countries as Levels.fyi slugs, e.g. united-states, india, united-kingdom, new-york-city-area, san-francisco-bay-area, bangalore. Empty = the company's main country.

## `startUrls` (type: `array`):

Any Levels.fyi salary page: /companies/google/salaries/software-engineer (optionally .../locations/india), /companies/google/salaries or /t/product-manager.

## `includeCompanyProfile` (type: `boolean`):

Adds website, LinkedIn, careers page, HQ, employees, ticker, funding type, vesting schedule and aliases to each row (no extra charge).

## `minSubmissions` (type: `integer`):

Leave out levels with fewer salary submissions, e.g. 10.

## `maxItems` (type: `integer`):

Most rows returned.

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

The default works for most runs.

## `aiInsights` (type: `boolean`):

Add an `insight` to each level: where its pay sits against the job family, a negotiation tip and how much data backs it; with a profile, how well it fits you.

## `aiProfile` (type: `string`):

Who you are or what you hire, e.g. "Senior backend engineer in Bangalore weighing an L5 offer". Adds a fit score.

## `aiLanguage` (type: `string`):

Insights are written in this language, whatever the source language.

## `maxInsights` (type: `integer`):

Insights are added to the first N levels.

## `aiProvider` (type: `string`):

Which AI does the analysis. Apify needs no key: the model's tokens are billed to your Apify account by Apify's AI gateway (a fraction of a cent per call with the default model). Any other provider uses your own key and bills you there.

## `aiApiKey` (type: `string`):

Your own key for the provider above (not needed for Apify). Sent only to that provider, never stored.

## `aiModel` (type: `string`):

Model name. Apify: an OpenRouter id like anthropic/claude-sonnet-... or google/gemini-... (default: the newest Claude Haiku listed, a light model since it runs once per result). Anthropic: default claude-opus-5-5. Others: required.

## `aiBaseUrl` (type: `string`):

Only for "Other OpenAI-compatible API", e.g. http://localhost:11434/v1 for Ollama.

## `debug` (type: `boolean`):

Save extra diagnostics with the run (for support requests).

## Actor input object example

```json
{
  "mode": "levels",
  "companies": [
    "google",
    "meta",
    "microsoft"
  ],
  "jobFamilies": [
    "software-engineer"
  ],
  "includeCompanyProfile": true,
  "maxItems": 500,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "US"
  },
  "aiInsights": false,
  "aiLanguage": "English",
  "maxInsights": 25,
  "aiProvider": "apify",
  "debug": false
}
```

# Actor output Schema

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

The produced items (default dataset items).

# 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": [
        "google",
        "meta",
        "microsoft"
    ],
    "jobFamilies": [
        "software-engineer"
    ],
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ],
        "apifyProxyCountry": "US"
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("tacps126/levels-fyi-salaries").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": [
        "google",
        "meta",
        "microsoft",
    ],
    "jobFamilies": ["software-engineer"],
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "US",
    },
}

# Run the Actor and wait for it to finish
run = client.actor("tacps126/levels-fyi-salaries").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": [
    "google",
    "meta",
    "microsoft"
  ],
  "jobFamilies": [
    "software-engineer"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "US"
  }
}' |
apify call tacps126/levels-fyi-salaries --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,tacps126/levels-fyi-salaries"
        }
    }
}
```

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/cqkYjN6F0rdrDcEkT/builds/09ZPazEmJkem1BZxb/openapi.json