Neural Search Jobs

curl --request POST \
  --url https://api.hirebase.org/v2/jobs/neural-search \
  --header 'Content-Type: application/json' \
  --data '
{
  "vector": {
    "job_ids": [
      "<string>"
    ],
    "artifact_id": "<string>",
    "query": "<string>",
    "vectors": [
      [
        123
      ]
    ],
    "score_threshold": 123
  },
  "lexical": {
    "job_titles": [
      "<string>"
    ],
    "keywords": [
      "<string>"
    ],
    "job_slug": "<string>",
    "company_slug": "<string>",
    "location_group": "<string>",
    "location_types": [
      "<string>"
    ],
    "geo_locations": [
      {
        "city": "<string>",
        "region": "<string>",
        "country": "<string>"
      }
    ],
    "experience": [
      "<string>"
    ],
    "yoe": {
      "min": 123,
      "max": 123
    },
    "include_yoe": "<string>",
    "company_types": [
      "<string>"
    ],
    "company_name": "<string>",
    "date_posted": "<string>",
    "days_ago": 123,
    "month": "<string>",
    "salary": {
      "min": 123,
      "max": 123
    },
    "include_no_salary": "<string>",
    "currency": "<string>",
    "job_types": [
      "<string>"
    ],
    "job_category": [
      "<string>"
    ],
    "industry": "<string>",
    "sub_industry": [
      "<string>"
    ],
    "visa": "<string>",
    "include_expired": "<string>",
    "hide_seen_jobs": "<string>",
    "user_id": "<string>",
    "job_board": [
      "<string>"
    ],
    "sort_by": "<string>",
    "sort_order": "<string>",
    "page": 123,
    "limit": 123
  }
}
'

import requests

url = "https://api.hirebase.org/v2/jobs/neural-search"

payload = {
    "vector": {
        "job_ids": ["<string>"],
        "artifact_id": "<string>",
        "query": "<string>",
        "vectors": [[123]],
        "score_threshold": 123
    },
    "lexical": {
        "job_titles": ["<string>"],
        "keywords": ["<string>"],
        "job_slug": "<string>",
        "company_slug": "<string>",
        "location_group": "<string>",
        "location_types": ["<string>"],
        "geo_locations": [
            {
                "city": "<string>",
                "region": "<string>",
                "country": "<string>"
            }
        ],
        "experience": ["<string>"],
        "yoe": {
            "min": 123,
            "max": 123
        },
        "include_yoe": "<string>",
        "company_types": ["<string>"],
        "company_name": "<string>",
        "date_posted": "<string>",
        "days_ago": 123,
        "month": "<string>",
        "salary": {
            "min": 123,
            "max": 123
        },
        "include_no_salary": "<string>",
        "currency": "<string>",
        "job_types": ["<string>"],
        "job_category": ["<string>"],
        "industry": "<string>",
        "sub_industry": ["<string>"],
        "visa": "<string>",
        "include_expired": "<string>",
        "hide_seen_jobs": "<string>",
        "user_id": "<string>",
        "job_board": ["<string>"],
        "sort_by": "<string>",
        "sort_order": "<string>",
        "page": 123,
        "limit": 123
    }
}
headers = {"Content-Type": "application/json"}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    vector: {
      job_ids: ['<string>'],
      artifact_id: '<string>',
      query: '<string>',
      vectors: [[123]],
      score_threshold: 123
    },
    lexical: {
      job_titles: ['<string>'],
      keywords: ['<string>'],
      job_slug: '<string>',
      company_slug: '<string>',
      location_group: '<string>',
      location_types: ['<string>'],
      geo_locations: [{city: '<string>', region: '<string>', country: '<string>'}],
      experience: ['<string>'],
      yoe: {min: 123, max: 123},
      include_yoe: '<string>',
      company_types: ['<string>'],
      company_name: '<string>',
      date_posted: '<string>',
      days_ago: 123,
      month: '<string>',
      salary: {min: 123, max: 123},
      include_no_salary: '<string>',
      currency: '<string>',
      job_types: ['<string>'],
      job_category: ['<string>'],
      industry: '<string>',
      sub_industry: ['<string>'],
      visa: '<string>',
      include_expired: '<string>',
      hide_seen_jobs: '<string>',
      user_id: '<string>',
      job_board: ['<string>'],
      sort_by: '<string>',
      sort_order: '<string>',
      page: 123,
      limit: 123
    }
  })
};

fetch('https://api.hirebase.org/v2/jobs/neural-search', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.hirebase.org/v2/jobs/neural-search",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'vector' => [
        'job_ids' => [
                '<string>'
        ],
        'artifact_id' => '<string>',
        'query' => '<string>',
        'vectors' => [
                [
                                123
                ]
        ],
        'score_threshold' => 123
    ],
    'lexical' => [
        'job_titles' => [
                '<string>'
        ],
        'keywords' => [
                '<string>'
        ],
        'job_slug' => '<string>',
        'company_slug' => '<string>',
        'location_group' => '<string>',
        'location_types' => [
                '<string>'
        ],
        'geo_locations' => [
                [
                                'city' => '<string>',
                                'region' => '<string>',
                                'country' => '<string>'
                ]
        ],
        'experience' => [
                '<string>'
        ],
        'yoe' => [
                'min' => 123,
                'max' => 123
        ],
        'include_yoe' => '<string>',
        'company_types' => [
                '<string>'
        ],
        'company_name' => '<string>',
        'date_posted' => '<string>',
        'days_ago' => 123,
        'month' => '<string>',
        'salary' => [
                'min' => 123,
                'max' => 123
        ],
        'include_no_salary' => '<string>',
        'currency' => '<string>',
        'job_types' => [
                '<string>'
        ],
        'job_category' => [
                '<string>'
        ],
        'industry' => '<string>',
        'sub_industry' => [
                '<string>'
        ],
        'visa' => '<string>',
        'include_expired' => '<string>',
        'hide_seen_jobs' => '<string>',
        'user_id' => '<string>',
        'job_board' => [
                '<string>'
        ],
        'sort_by' => '<string>',
        'sort_order' => '<string>',
        'page' => 123,
        'limit' => 123
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.hirebase.org/v2/jobs/neural-search"

	payload := strings.NewReader("{\n  \"vector\": {\n    \"job_ids\": [\n      \"<string>\"\n    ],\n    \"artifact_id\": \"<string>\",\n    \"query\": \"<string>\",\n    \"vectors\": [\n      [\n        123\n      ]\n    ],\n    \"score_threshold\": 123\n  },\n  \"lexical\": {\n    \"job_titles\": [\n      \"<string>\"\n    ],\n    \"keywords\": [\n      \"<string>\"\n    ],\n    \"job_slug\": \"<string>\",\n    \"company_slug\": \"<string>\",\n    \"location_group\": \"<string>\",\n    \"location_types\": [\n      \"<string>\"\n    ],\n    \"geo_locations\": [\n      {\n        \"city\": \"<string>\",\n        \"region\": \"<string>\",\n        \"country\": \"<string>\"\n      }\n    ],\n    \"experience\": [\n      \"<string>\"\n    ],\n    \"yoe\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_yoe\": \"<string>\",\n    \"company_types\": [\n      \"<string>\"\n    ],\n    \"company_name\": \"<string>\",\n    \"date_posted\": \"<string>\",\n    \"days_ago\": 123,\n    \"month\": \"<string>\",\n    \"salary\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_no_salary\": \"<string>\",\n    \"currency\": \"<string>\",\n    \"job_types\": [\n      \"<string>\"\n    ],\n    \"job_category\": [\n      \"<string>\"\n    ],\n    \"industry\": \"<string>\",\n    \"sub_industry\": [\n      \"<string>\"\n    ],\n    \"visa\": \"<string>\",\n    \"include_expired\": \"<string>\",\n    \"hide_seen_jobs\": \"<string>\",\n    \"user_id\": \"<string>\",\n    \"job_board\": [\n      \"<string>\"\n    ],\n    \"sort_by\": \"<string>\",\n    \"sort_order\": \"<string>\",\n    \"page\": 123,\n    \"limit\": 123\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.hirebase.org/v2/jobs/neural-search")
  .header("Content-Type", "application/json")
  .body("{\n  \"vector\": {\n    \"job_ids\": [\n      \"<string>\"\n    ],\n    \"artifact_id\": \"<string>\",\n    \"query\": \"<string>\",\n    \"vectors\": [\n      [\n        123\n      ]\n    ],\n    \"score_threshold\": 123\n  },\n  \"lexical\": {\n    \"job_titles\": [\n      \"<string>\"\n    ],\n    \"keywords\": [\n      \"<string>\"\n    ],\n    \"job_slug\": \"<string>\",\n    \"company_slug\": \"<string>\",\n    \"location_group\": \"<string>\",\n    \"location_types\": [\n      \"<string>\"\n    ],\n    \"geo_locations\": [\n      {\n        \"city\": \"<string>\",\n        \"region\": \"<string>\",\n        \"country\": \"<string>\"\n      }\n    ],\n    \"experience\": [\n      \"<string>\"\n    ],\n    \"yoe\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_yoe\": \"<string>\",\n    \"company_types\": [\n      \"<string>\"\n    ],\n    \"company_name\": \"<string>\",\n    \"date_posted\": \"<string>\",\n    \"days_ago\": 123,\n    \"month\": \"<string>\",\n    \"salary\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_no_salary\": \"<string>\",\n    \"currency\": \"<string>\",\n    \"job_types\": [\n      \"<string>\"\n    ],\n    \"job_category\": [\n      \"<string>\"\n    ],\n    \"industry\": \"<string>\",\n    \"sub_industry\": [\n      \"<string>\"\n    ],\n    \"visa\": \"<string>\",\n    \"include_expired\": \"<string>\",\n    \"hide_seen_jobs\": \"<string>\",\n    \"user_id\": \"<string>\",\n    \"job_board\": [\n      \"<string>\"\n    ],\n    \"sort_by\": \"<string>\",\n    \"sort_order\": \"<string>\",\n    \"page\": 123,\n    \"limit\": 123\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.hirebase.org/v2/jobs/neural-search")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"vector\": {\n    \"job_ids\": [\n      \"<string>\"\n    ],\n    \"artifact_id\": \"<string>\",\n    \"query\": \"<string>\",\n    \"vectors\": [\n      [\n        123\n      ]\n    ],\n    \"score_threshold\": 123\n  },\n  \"lexical\": {\n    \"job_titles\": [\n      \"<string>\"\n    ],\n    \"keywords\": [\n      \"<string>\"\n    ],\n    \"job_slug\": \"<string>\",\n    \"company_slug\": \"<string>\",\n    \"location_group\": \"<string>\",\n    \"location_types\": [\n      \"<string>\"\n    ],\n    \"geo_locations\": [\n      {\n        \"city\": \"<string>\",\n        \"region\": \"<string>\",\n        \"country\": \"<string>\"\n      }\n    ],\n    \"experience\": [\n      \"<string>\"\n    ],\n    \"yoe\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_yoe\": \"<string>\",\n    \"company_types\": [\n      \"<string>\"\n    ],\n    \"company_name\": \"<string>\",\n    \"date_posted\": \"<string>\",\n    \"days_ago\": 123,\n    \"month\": \"<string>\",\n    \"salary\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_no_salary\": \"<string>\",\n    \"currency\": \"<string>\",\n    \"job_types\": [\n      \"<string>\"\n    ],\n    \"job_category\": [\n      \"<string>\"\n    ],\n    \"industry\": \"<string>\",\n    \"sub_industry\": [\n      \"<string>\"\n    ],\n    \"visa\": \"<string>\",\n    \"include_expired\": \"<string>\",\n    \"hide_seen_jobs\": \"<string>\",\n    \"user_id\": \"<string>\",\n    \"job_board\": [\n      \"<string>\"\n    ],\n    \"sort_by\": \"<string>\",\n    \"sort_order\": \"<string>\",\n    \"page\": 123,\n    \"limit\": 123\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "jobs": [
    {
      "_id": "<string>",
      "job_title": "<string>",
      "job_title_raw": "<string>",
      "description": "<string>",
      "application_link": "<string>",
      "job_categories": [
        {}
      ],
      "job_type": "<string>",
      "location_type": "<string>",
      "location_raw": "<string>",
      "locations": [
        {
          "city": "<string>",
          "region": "<string>",
          "country": "<string>"
        }
      ],
      "salary_range": {
        "min": 123,
        "max": 123,
        "currency": "<string>",
        "period": "<string>"
      },
      "yoe_range": {
        "min": 123,
        "max": 123
      },
      "experience_level": {},
      "education_level": "<string>",
      "skills": [
        "<string>"
      ],
      "technologies": [
        "<string>"
      ],
      "benefits": [
        "<string>"
      ],
      "requirements_summary": "<string>",
      "team": "<string>",
      "language": "<string>",
      "visa_sponsored": true,
      "recruiter_agency": true,
      "offers_equity": true,
      "date_posted": "<string>",
      "job_board": "<string>",
      "job_board_link": "<string>",
      "job_slug": "<string>",
      "company_name": "<string>",
      "company_slug": "<string>",
      "company_link": "<string>",
      "company_logo": "<string>",
      "md5_hash": "<string>",
      "platform_job_id": "<string>",
      "contact_email": {},
      "contact_phone": {},
      "coolness_score": 123,
      "flexibility_score": 123,
      "compensation_value_score": 123,
      "benefits_score": 123,
      "impact_autonomy_score": 123,
      "prestige_score": 123,
      "growth_score": 123,
      "meta_completeness": true,
      "meta_targetability": 123,
      "company_data": {
        "description_summary": "<string>",
        "linkedin_link": {},
        "services": [
          "<string>"
        ],
        "size_range": {
          "min": 123,
          "max": 123
        },
        "industries": [
          {}
        ],
        "subindustries": [
          {}
        ],
        "type": {},
        "is_recruiting_agency": {},
        "is_3rd_party_agency": {}
      }
    }
  ],
  "total_count": 123,
  "page": 123,
  "limit": 123,
  "total_pages": 123
}

POST

jobs

neural-search

Neural Search Jobs

curl --request POST \
  --url https://api.hirebase.org/v2/jobs/neural-search \
  --header 'Content-Type: application/json' \
  --data '
{
  "vector": {
    "job_ids": [
      "<string>"
    ],
    "artifact_id": "<string>",
    "query": "<string>",
    "vectors": [
      [
        123
      ]
    ],
    "score_threshold": 123
  },
  "lexical": {
    "job_titles": [
      "<string>"
    ],
    "keywords": [
      "<string>"
    ],
    "job_slug": "<string>",
    "company_slug": "<string>",
    "location_group": "<string>",
    "location_types": [
      "<string>"
    ],
    "geo_locations": [
      {
        "city": "<string>",
        "region": "<string>",
        "country": "<string>"
      }
    ],
    "experience": [
      "<string>"
    ],
    "yoe": {
      "min": 123,
      "max": 123
    },
    "include_yoe": "<string>",
    "company_types": [
      "<string>"
    ],
    "company_name": "<string>",
    "date_posted": "<string>",
    "days_ago": 123,
    "month": "<string>",
    "salary": {
      "min": 123,
      "max": 123
    },
    "include_no_salary": "<string>",
    "currency": "<string>",
    "job_types": [
      "<string>"
    ],
    "job_category": [
      "<string>"
    ],
    "industry": "<string>",
    "sub_industry": [
      "<string>"
    ],
    "visa": "<string>",
    "include_expired": "<string>",
    "hide_seen_jobs": "<string>",
    "user_id": "<string>",
    "job_board": [
      "<string>"
    ],
    "sort_by": "<string>",
    "sort_order": "<string>",
    "page": 123,
    "limit": 123
  }
}
'

import requests

url = "https://api.hirebase.org/v2/jobs/neural-search"

payload = {
    "vector": {
        "job_ids": ["<string>"],
        "artifact_id": "<string>",
        "query": "<string>",
        "vectors": [[123]],
        "score_threshold": 123
    },
    "lexical": {
        "job_titles": ["<string>"],
        "keywords": ["<string>"],
        "job_slug": "<string>",
        "company_slug": "<string>",
        "location_group": "<string>",
        "location_types": ["<string>"],
        "geo_locations": [
            {
                "city": "<string>",
                "region": "<string>",
                "country": "<string>"
            }
        ],
        "experience": ["<string>"],
        "yoe": {
            "min": 123,
            "max": 123
        },
        "include_yoe": "<string>",
        "company_types": ["<string>"],
        "company_name": "<string>",
        "date_posted": "<string>",
        "days_ago": 123,
        "month": "<string>",
        "salary": {
            "min": 123,
            "max": 123
        },
        "include_no_salary": "<string>",
        "currency": "<string>",
        "job_types": ["<string>"],
        "job_category": ["<string>"],
        "industry": "<string>",
        "sub_industry": ["<string>"],
        "visa": "<string>",
        "include_expired": "<string>",
        "hide_seen_jobs": "<string>",
        "user_id": "<string>",
        "job_board": ["<string>"],
        "sort_by": "<string>",
        "sort_order": "<string>",
        "page": 123,
        "limit": 123
    }
}
headers = {"Content-Type": "application/json"}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    vector: {
      job_ids: ['<string>'],
      artifact_id: '<string>',
      query: '<string>',
      vectors: [[123]],
      score_threshold: 123
    },
    lexical: {
      job_titles: ['<string>'],
      keywords: ['<string>'],
      job_slug: '<string>',
      company_slug: '<string>',
      location_group: '<string>',
      location_types: ['<string>'],
      geo_locations: [{city: '<string>', region: '<string>', country: '<string>'}],
      experience: ['<string>'],
      yoe: {min: 123, max: 123},
      include_yoe: '<string>',
      company_types: ['<string>'],
      company_name: '<string>',
      date_posted: '<string>',
      days_ago: 123,
      month: '<string>',
      salary: {min: 123, max: 123},
      include_no_salary: '<string>',
      currency: '<string>',
      job_types: ['<string>'],
      job_category: ['<string>'],
      industry: '<string>',
      sub_industry: ['<string>'],
      visa: '<string>',
      include_expired: '<string>',
      hide_seen_jobs: '<string>',
      user_id: '<string>',
      job_board: ['<string>'],
      sort_by: '<string>',
      sort_order: '<string>',
      page: 123,
      limit: 123
    }
  })
};

fetch('https://api.hirebase.org/v2/jobs/neural-search', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.hirebase.org/v2/jobs/neural-search",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'vector' => [
        'job_ids' => [
                '<string>'
        ],
        'artifact_id' => '<string>',
        'query' => '<string>',
        'vectors' => [
                [
                                123
                ]
        ],
        'score_threshold' => 123
    ],
    'lexical' => [
        'job_titles' => [
                '<string>'
        ],
        'keywords' => [
                '<string>'
        ],
        'job_slug' => '<string>',
        'company_slug' => '<string>',
        'location_group' => '<string>',
        'location_types' => [
                '<string>'
        ],
        'geo_locations' => [
                [
                                'city' => '<string>',
                                'region' => '<string>',
                                'country' => '<string>'
                ]
        ],
        'experience' => [
                '<string>'
        ],
        'yoe' => [
                'min' => 123,
                'max' => 123
        ],
        'include_yoe' => '<string>',
        'company_types' => [
                '<string>'
        ],
        'company_name' => '<string>',
        'date_posted' => '<string>',
        'days_ago' => 123,
        'month' => '<string>',
        'salary' => [
                'min' => 123,
                'max' => 123
        ],
        'include_no_salary' => '<string>',
        'currency' => '<string>',
        'job_types' => [
                '<string>'
        ],
        'job_category' => [
                '<string>'
        ],
        'industry' => '<string>',
        'sub_industry' => [
                '<string>'
        ],
        'visa' => '<string>',
        'include_expired' => '<string>',
        'hide_seen_jobs' => '<string>',
        'user_id' => '<string>',
        'job_board' => [
                '<string>'
        ],
        'sort_by' => '<string>',
        'sort_order' => '<string>',
        'page' => 123,
        'limit' => 123
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.hirebase.org/v2/jobs/neural-search"

	payload := strings.NewReader("{\n  \"vector\": {\n    \"job_ids\": [\n      \"<string>\"\n    ],\n    \"artifact_id\": \"<string>\",\n    \"query\": \"<string>\",\n    \"vectors\": [\n      [\n        123\n      ]\n    ],\n    \"score_threshold\": 123\n  },\n  \"lexical\": {\n    \"job_titles\": [\n      \"<string>\"\n    ],\n    \"keywords\": [\n      \"<string>\"\n    ],\n    \"job_slug\": \"<string>\",\n    \"company_slug\": \"<string>\",\n    \"location_group\": \"<string>\",\n    \"location_types\": [\n      \"<string>\"\n    ],\n    \"geo_locations\": [\n      {\n        \"city\": \"<string>\",\n        \"region\": \"<string>\",\n        \"country\": \"<string>\"\n      }\n    ],\n    \"experience\": [\n      \"<string>\"\n    ],\n    \"yoe\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_yoe\": \"<string>\",\n    \"company_types\": [\n      \"<string>\"\n    ],\n    \"company_name\": \"<string>\",\n    \"date_posted\": \"<string>\",\n    \"days_ago\": 123,\n    \"month\": \"<string>\",\n    \"salary\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_no_salary\": \"<string>\",\n    \"currency\": \"<string>\",\n    \"job_types\": [\n      \"<string>\"\n    ],\n    \"job_category\": [\n      \"<string>\"\n    ],\n    \"industry\": \"<string>\",\n    \"sub_industry\": [\n      \"<string>\"\n    ],\n    \"visa\": \"<string>\",\n    \"include_expired\": \"<string>\",\n    \"hide_seen_jobs\": \"<string>\",\n    \"user_id\": \"<string>\",\n    \"job_board\": [\n      \"<string>\"\n    ],\n    \"sort_by\": \"<string>\",\n    \"sort_order\": \"<string>\",\n    \"page\": 123,\n    \"limit\": 123\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://api.hirebase.org/v2/jobs/neural-search")
  .header("Content-Type", "application/json")
  .body("{\n  \"vector\": {\n    \"job_ids\": [\n      \"<string>\"\n    ],\n    \"artifact_id\": \"<string>\",\n    \"query\": \"<string>\",\n    \"vectors\": [\n      [\n        123\n      ]\n    ],\n    \"score_threshold\": 123\n  },\n  \"lexical\": {\n    \"job_titles\": [\n      \"<string>\"\n    ],\n    \"keywords\": [\n      \"<string>\"\n    ],\n    \"job_slug\": \"<string>\",\n    \"company_slug\": \"<string>\",\n    \"location_group\": \"<string>\",\n    \"location_types\": [\n      \"<string>\"\n    ],\n    \"geo_locations\": [\n      {\n        \"city\": \"<string>\",\n        \"region\": \"<string>\",\n        \"country\": \"<string>\"\n      }\n    ],\n    \"experience\": [\n      \"<string>\"\n    ],\n    \"yoe\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_yoe\": \"<string>\",\n    \"company_types\": [\n      \"<string>\"\n    ],\n    \"company_name\": \"<string>\",\n    \"date_posted\": \"<string>\",\n    \"days_ago\": 123,\n    \"month\": \"<string>\",\n    \"salary\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_no_salary\": \"<string>\",\n    \"currency\": \"<string>\",\n    \"job_types\": [\n      \"<string>\"\n    ],\n    \"job_category\": [\n      \"<string>\"\n    ],\n    \"industry\": \"<string>\",\n    \"sub_industry\": [\n      \"<string>\"\n    ],\n    \"visa\": \"<string>\",\n    \"include_expired\": \"<string>\",\n    \"hide_seen_jobs\": \"<string>\",\n    \"user_id\": \"<string>\",\n    \"job_board\": [\n      \"<string>\"\n    ],\n    \"sort_by\": \"<string>\",\n    \"sort_order\": \"<string>\",\n    \"page\": 123,\n    \"limit\": 123\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.hirebase.org/v2/jobs/neural-search")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Content-Type"] = 'application/json'
request.body = "{\n  \"vector\": {\n    \"job_ids\": [\n      \"<string>\"\n    ],\n    \"artifact_id\": \"<string>\",\n    \"query\": \"<string>\",\n    \"vectors\": [\n      [\n        123\n      ]\n    ],\n    \"score_threshold\": 123\n  },\n  \"lexical\": {\n    \"job_titles\": [\n      \"<string>\"\n    ],\n    \"keywords\": [\n      \"<string>\"\n    ],\n    \"job_slug\": \"<string>\",\n    \"company_slug\": \"<string>\",\n    \"location_group\": \"<string>\",\n    \"location_types\": [\n      \"<string>\"\n    ],\n    \"geo_locations\": [\n      {\n        \"city\": \"<string>\",\n        \"region\": \"<string>\",\n        \"country\": \"<string>\"\n      }\n    ],\n    \"experience\": [\n      \"<string>\"\n    ],\n    \"yoe\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_yoe\": \"<string>\",\n    \"company_types\": [\n      \"<string>\"\n    ],\n    \"company_name\": \"<string>\",\n    \"date_posted\": \"<string>\",\n    \"days_ago\": 123,\n    \"month\": \"<string>\",\n    \"salary\": {\n      \"min\": 123,\n      \"max\": 123\n    },\n    \"include_no_salary\": \"<string>\",\n    \"currency\": \"<string>\",\n    \"job_types\": [\n      \"<string>\"\n    ],\n    \"job_category\": [\n      \"<string>\"\n    ],\n    \"industry\": \"<string>\",\n    \"sub_industry\": [\n      \"<string>\"\n    ],\n    \"visa\": \"<string>\",\n    \"include_expired\": \"<string>\",\n    \"hide_seen_jobs\": \"<string>\",\n    \"user_id\": \"<string>\",\n    \"job_board\": [\n      \"<string>\"\n    ],\n    \"sort_by\": \"<string>\",\n    \"sort_order\": \"<string>\",\n    \"page\": 123,\n    \"limit\": 123\n  }\n}"

response = http.request(request)
puts response.read_body

{
  "jobs": [
    {
      "_id": "<string>",
      "job_title": "<string>",
      "job_title_raw": "<string>",
      "description": "<string>",
      "application_link": "<string>",
      "job_categories": [
        {}
      ],
      "job_type": "<string>",
      "location_type": "<string>",
      "location_raw": "<string>",
      "locations": [
        {
          "city": "<string>",
          "region": "<string>",
          "country": "<string>"
        }
      ],
      "salary_range": {
        "min": 123,
        "max": 123,
        "currency": "<string>",
        "period": "<string>"
      },
      "yoe_range": {
        "min": 123,
        "max": 123
      },
      "experience_level": {},
      "education_level": "<string>",
      "skills": [
        "<string>"
      ],
      "technologies": [
        "<string>"
      ],
      "benefits": [
        "<string>"
      ],
      "requirements_summary": "<string>",
      "team": "<string>",
      "language": "<string>",
      "visa_sponsored": true,
      "recruiter_agency": true,
      "offers_equity": true,
      "date_posted": "<string>",
      "job_board": "<string>",
      "job_board_link": "<string>",
      "job_slug": "<string>",
      "company_name": "<string>",
      "company_slug": "<string>",
      "company_link": "<string>",
      "company_logo": "<string>",
      "md5_hash": "<string>",
      "platform_job_id": "<string>",
      "contact_email": {},
      "contact_phone": {},
      "coolness_score": 123,
      "flexibility_score": 123,
      "compensation_value_score": 123,
      "benefits_score": 123,
      "impact_autonomy_score": 123,
      "prestige_score": 123,
      "growth_score": 123,
      "meta_completeness": true,
      "meta_targetability": 123,
      "company_data": {
        "description_summary": "<string>",
        "linkedin_link": {},
        "services": [
          "<string>"
        ],
        "size_range": {
          "min": 123,
          "max": 123
        },
        "industries": [
          {}
        ],
        "subindustries": [
          {}
        ],
        "type": {},
        "is_recruiting_agency": {},
        "is_3rd_party_agency": {}
      }
    }
  ],
  "total_count": 123,
  "page": 123,
  "limit": 123,
  "total_pages": 123
}

This endpoint enables you to perform hybrid searches: apply familiar filters (titles, locations, salary, etc.) while simultaneously ranking results by vector similarity to a text query or embedding.

Endpoint

POST /v2/jobs/neural-search

Request Body

Note:

You can supply only vector, only lexical, or both; at least one must be present.
If you include both, results are ordered by combined ranking (semantic score then lexical rank).

vector

object

Parameters for semantic, embedding-based search

Show child attributes

job_ids

string[]

Optional list of explicit job IDs to constrain the semantic search.

artifact_id

string

ID of the embedding artifact (e.g., resume) to use. Use the _id returned by Upload Resume.

query

string

Semantic text query to be encoded into a vector for similarity matching.

vectors

number[][]

Explicit embedding vectors (each must be 768 elements long) to compare against job vectors.

score_threshold

number

Minimum similarity score (0.0–1.0) for a job to appear in jobs. Defaults to 0.0. Note: filters the returned jobs only — total_count still reflects the endpoint cap.

lexical

object

Traditional filtering parameters

Show child attributes

job_titles

string[]

Array of job titles to search for (e.g., ["Software Engineer", "Data Scientist"]).

keywords

string[]

Array of keywords to match within job descriptions.

job_slug

string

Filter by a specific job’s slug (deep-link identifier).

company_slug

string

Filter by a specific company’s slug.

location_group

string

Predefined location set (e.g., "Bay_Area").

⚠️ Not currently applied — this filter is accepted but does not affect results yet. Use geo_locations for location filtering.

location_types

string[]

Work arrangements to include. Accepted values: "Remote", "Hybrid", "In-Person".

geo_locations

object[]

Array of geographic filters.

Show child attributes

city

string

City name

region

string

State, region or province

country

string

Country name

experience

string[]

Experience level categories. Accepted values: "Entry", "Junior", "Mid", "Senior", "Executive".

yoe

object

Years-of-experience range.

Show child attributes

min

number

Minimum years

max

number

Maximum years

include_yoe

string

Set to "true" to include jobs without specified years of experience.

company_types

string[]

Filter jobs by the hiring company’s headcount bucket. Accepted values: "1-10", "11-50", "51-200", "201-500", "501-1000", "1001-5000", "5001-10000", "10000+". Pass multiple values to combine ranges (e.g., ["11-50", "51-200"]).

This parameter is named company_types for historical reasons but currently filters by company size. A separate classification filter (Public Company / Non-Profit / etc.) will be added in a future API update.

company_name

string

Exact company name filter.

date_posted

string

Relative timeframe (e.g., "today", "last_week", "last_month").

days_ago

number

Jobs posted in the last n days (e.g., 7).

month

string

Specific month in YYYY-MM format (e.g., "2023-12").

⚠️ Not currently applied — this filter is accepted but does not affect results yet. Use days_ago or date_posted to filter by posting time.

salary

object

Salary range filter.

Show child attributes

min

number

Minimum salary

max

number

Maximum salary

include_no_salary

string

Set to "true" to include listings without salary data.

currency

string

Three-letter currency code (e.g., "USD").

job_types

string[]

Array of employment types. Accepted values: "Full Time", "Part Time", "Contract", "Internship".

The "Contract" value matches roles whose returned job_type is "Contract / Temporary" — request token and response label differ.

The correct field name is job_types (plural). Using job_type (singular) is silently ignored — the request succeeds but the filter is not applied.

job_category

string[]

Specific job categories (e.g., ["Data Science"]).

industry

string

Industry to filter by (e.g., "Tech, Software & IT Services", "Healthcare").

industry must be a single string, not an array. Passing an array may result in a 500 error.

sub_industry

string[]

More specific industry categories.

visa

string

Set to "true" to only include visa-sponsored roles.

include_expired

string

Set to "true" to include expired listings.

hide_seen_jobs

string

Set to "true" to omit jobs the user has already viewed.

user_id

string

User’s MongoDB ObjectId for personalized filtering.

job_board

string[]

Source job boards (e.g., ["iCIMS","Greenhouse"]).

sort_by

string

Field to sort lexical results by. Accepted values: "relevance", "date_posted", "salary", "company", "yoe". Invalid values are silently ignored.

sort_order

string

"asc" or "desc".

page

number

default:"1"

Page number

limit

number

default:"10"

Results per page

Response

jobs

array

Array of job objects matching the query.

Show child attributes

_id

string

Unique job identifier

job_title

string

Job title

job_title_raw

string

Unparsed job title as scraped from the source.

description

string

Full job description (HTML or text)

application_link

string

URL to apply

job_categories

array

Tags/categories for the role

job_type

string

Employment type. One of: "Full Time", "Part Time", "Contract / Temporary", "Internship".

location_type

string

Work arrangement

location_raw

string

Raw location string from the source job board (before normalization into locations).

locations

array

Array of location objects

Show child attributes

city

string

City name

region

string

State or province

country

string

Country

salary_range

object|null

Offered salary range

Show child attributes

min

number

Minimum salary

max

number

Maximum salary

currency

string

Currency code

period

string

Pay period for the salary range. Observed values: "yearly", "monthly", "daily", "hourly".

This field is not fully normalized today — you may also see "year" (≡ "yearly") and "hour" (≡ "hourly"). Treat those as equivalent until normalized.

yoe_range

object

Required years of experience

Show child attributes

min

number

Min years

max

number

Max years

experience_level

string | null

Parsed experience tier for the role (e.g., "Senior"). May be null when not inferred.

education_level

string

Required education level. One of: "No Education Required", "High school degree", "Associate degree", "Bachelor's degree", "Master's degree", "Doctoral degree".

skills

string[]

List of skills mentioned in the job description

technologies

string[]

List of technologies mentioned in the job description

benefits

string[]

List of benefits mentioned in the job description

requirements_summary

string

Brief qualifications summary

team

string

Team at the company hiring for the position

language

string

Language the job posting is in

visa_sponsored

boolean

Whether visa sponsorship is offered

recruiter_agency

boolean

Indicates whether the listing was posted by a recruiting agency

offers_equity

boolean

Whether the listing mentions equity compensation.

date_posted

string

Posting date (format: YYYY-MM-DD).

job_board

string

Source job board

job_board_link

string

URL of the job board

job_slug

string

Deep-link slug for the job

company_name

string

Name of hiring company

company_slug

string

Company slug

company_link

string

Company website

company_logo

string

URL to company logo

md5_hash

string

Content hash of the listing.

platform_job_id

string

The source ATS’s own job identifier.

contact_email

string | null

Contact email for the listing, when available. Paid users only.

contact_phone

string | null

Contact phone number for the listing, when available. Paid users only.

Dimension scores — coolness_score, flexibility_score, compensation_value_score, benefits_score, impact_autonomy_score, prestige_score, and growth_score each use a 0–10 scale (higher is better).

coolness_score

number

Company/role “coolness” rating (0–10).

flexibility_score

number

Work-flexibility rating (0–10).

compensation_value_score

number

Compensation competitiveness rating (0–10).

benefits_score

number

Benefits package rating (0–10).

impact_autonomy_score

number

Role-level impact and autonomy rating (0–10).

prestige_score

number

Company/role prestige rating (0–10).

growth_score

number

Career growth / learning opportunity rating (0–10).

meta_completeness

boolean

Whether the parsed listing metadata is considered complete.

meta_targetability

number

Internal signal (0–1) reflecting how targetable/complete the listing is for matching.

company_data

object

Enriched company profile

Show child attributes

description_summary

string

Short company description

linkedin_link

string|null

LinkedIn URL

services

string[]

List of services that the company provides

size_range

object|null

Employee count range

Show child attributes

min

number

Min headcount

max

number

Max headcount

industries

array

Industry sectors

subindustries

array

Detailed industry categories

type

string | null

Categorical company type (e.g., "Startup", "Enterprise").

is_recruiting_agency

boolean | null

Whether the company is a recruiting/talent agency.

is_3rd_party_agency

boolean | null

Whether the company is a third-party agency.

total_count

number

Total number of matching jobs. Capped at 2,500 for this endpoint.

page

number

Current page number

limit

number

Number of results returned

total_pages

number

Total pages available

Rate limit: 4 requests/second on search endpoints. See Error Handling.Note: Results are ranked by semantic similarity internally, but a per-job vector_score field is not currently returned in the response.

Example Request

curl -X POST https://api.hirebase.org/v2/jobs/neural-search \
  -H "Content-Type: application/json" \
  -H "x-api-key: YOUR_API_KEY" \
  -d '{
    "vector": {
      "query": "senior backend engineer building distributed systems with Python and Kubernetes"
    },
    "lexical": {
      "location_types": ["Remote", "Hybrid"],
      "experience": ["Senior"],
      "industry": "Tech, Software & IT Services",
      "days_ago": 30,
      "limit": 10
    }
  }'

{
  "vector": {
    "query": "machine learning engineer"
  },
  "lexical": {
    "location_group": "Bay_Area",
    "experience": ["Mid", "Senior"],
    "yoe": {"min": 2, "max": 5},
    "job_types": ["Full Time"],
    "industry": "Tech, Software & IT Services",
    "page": 1,
    "limit": 5
  }
}

Example Response

{
  "jobs": [
    {
      "_id": "6a2f14a48bea0df96e26ac7b",
      "company_name": "CompanyXYZ",
      "job_title": "Senior Python Engineer",
      "job_title_raw": "Senior Python Engineer - Remote",
      "description": "<p>… cleaned/summarized description …</p>",
      "application_link": "https://jobs.workable.com/view/nqSdYtJwQ/...",
      "job_categories": ["Software Engineer Jobs", "Engineering Jobs", "Information Technology Jobs"],
      "job_type": "Full Time",
      "location_type": "Remote",
      "location_raw": "TELECOMMUTE; British Columbia, Canada",
      "locations": [
        {
          "city": null,
          "region": null,
          "country": "Canada",
          "coordinates": {"type": "Point", "coordinates": [-123.12, 49.28]},
          "bbox": [-123.2, 49.0, -122.9, 49.3],
          "address": "British Columbia, Canada"
        }
      ],
      "salary_range": {"min": 150000, "max": 210000, "currency": "USD", "period": "yearly"},
      "yoe_range": {"min": 2, "max": 5},
      "experience_level": "Senior",
      "education_level": "Bachelor's degree",
      "skills": ["Python", "FastAPI", "Distributed systems"],
      "technologies": ["Python", "PostgreSQL", "AWS"],
      "benefits": ["401k matching", "Remote-first", "Equity"],
      "requirements_summary": "5+ years Python; distributed systems experience",
      "team": "Platform Engineering",
      "language": "en",
      "visa_sponsored": false,
      "recruiter_agency": false,
      "offers_equity": false,
      "date_posted": "2026-06-07",
      "job_board": "workable",
      "job_board_link": "https://jobs.workable.com/company/...",
      "job_slug": "senior-python-engineer-17",
      "company_slug": "companyxyz",
      "company_link": "companyxyz.com",
      "company_logo": "https://logos.hirebase.org/.../companyxyz-320x320-q95.jpg",
      "md5_hash": "d6b5d4e7b99d23b082b46e49c22c168f",
      "platform_job_id": "ad88b6ba-a905-4850-ad79-73beb0e97766",
      "coolness_score": 6.4,
      "flexibility_score": 6.1,
      "compensation_value_score": 6.0,
      "benefits_score": 5.0,
      "impact_autonomy_score": 7.1,
      "prestige_score": 5.2,
      "growth_score": 6.2,
      "meta_completeness": false,
      "meta_targetability": 0.8,
      "company_data": {
        "description_summary": "CompanyXYZ builds …",
        "linkedin_link": "https://www.linkedin.com/company/companyxyz",
        "size_range": {"min": 51, "max": 200},
        "industries": ["Tech, Software & IT Services"],
        "subindustries": ["AI & ML"],
        "services": ["Platform", "APIs"],
        "type": "Startup",
        "is_recruiting_agency": false,
        "is_3rd_party_agency": false
      }
    }
  ],
  "total_count": 23,
  "page": 1,
  "limit": 5,
  "total_pages": 5
}

Error Responses

422 Unprocessable Entity

Returned when the request is malformed or contains invalid parameters.

500 Internal Server Error

Returned when an unexpected server-side error occurs.

403 Forbidden

Returned if you do not have access to this feature.

Search Jobs (GET)

Vector Search Jobs

Jobs API

Hiring Manager API

Companies API

Insights API

Reference Data API

Resumes

Tasks API

Error Handling

Neural Search Jobs

Endpoint

Request Body

Response

Example Request

Example Response

Error Responses

​Endpoint

​Request Body

​Response

​Example Request

​Example Response

​Error Responses

Endpoint

Request Body

Response

Example Request

Example Response

Error Responses