Step 1. Submit the AI Job request
Endpoint: Post - /api/v1/hr/parse_resume
REQUEST EXAMPLE:
curl --location 'https://sharpapi.com/api/v1/hr/parse_resume' \
--header 'Accept: application/json' \
-H "Authorization: Bearer YOUR_API_TOKEN" \
--form 'file=@"Resume.pdf"' \
--form 'language="English"'
--
RESPONSE EXAMPLE:
{
"status_url": "https://sharpapi.com/api/v1/content/translate/job/status/5de4887a-0dfd-49b6-8edb-9280e468c210",
"job_id": "5de4887a-0dfd-49b6-8edb-9280e468c210"
}
Step 2. Monitor & Fetch AI Job Results
Endpoint: GET - /v1/hr/parse_resume/job/status/:uuid
An endpoint is used to check on the progress of the requested API job.
RESULT EXAMPLE:
{
"data": {
"type": "api_job_result",
"id": "50fa96a0-3e34-4323-be84-6ed602b00925",
"attributes": {
"status": "success",
"type": "hr_parse_resume",
"result": {
"candidate_name": "Jack Doe",
"candidate_email": "johndoe@gmail.com",
"candidate_phone": "+1 888 888 8888",
"candidate_address": "",
"candidate_language": "English",
"candidate_spoken_languages": [
"English"
],
"candidate_honors_and_awards": [
"Third best project in Machine Learning Practical by IBM"
],
"candidate_courses_and_certifications": [],
"candidate_linkedin": "",
"candidate_github": "",
"candidate_twitter": "",
"candidate_website": "",
"candidate_date_of_birth": null,
"candidate_nationality": "",
"candidate_summary_objective": "",
"work_authorization": "",
"years_of_experience": 2,
"approximate_age": null,
"brief_summary": "John Doe is a skilled software engineer with experience in Android development and a strong academic background in artificial intelligence and computer science.",
"drivers_licenses": [],
"interests_hobbies": [],
"projects": [
{
"project_name": "Image Classification",
"description": "Classified images of handwritten digits and letters from the MNIST and EMNIST datasets using deep neural networks. Implemented models with different activation functions, weight initialization strategies, and learning rules.",
"url": ""
},
{
"project_name": "Speaker Independent Digit Recognition",
"description": "Recorded voiced English digits and parameterized the collected waveform files as MFCCs. Constructed a speaker-dependent, and -independent speech recognizer using the Hidden Markov Model Toolkit (HTK).",
"url": ""
}
],
"volunteer_experience": [],
"publications": [],
"references": [],
"positions": [
{
"position_name": "Software Engineer Internship",
"company_name": "Google Inc.",
"country": "Japan",
"start_date": "2017-05-01",
"end_date": "2017-07-31",
"skills": [
"Android",
"Google Maps",
"Interactive screenshot code generator"
],
"job_details": "Designed and implemented an interactive screenshot code generator for Android Google Maps."
},
{
"position_name": "Visiting Student Research Internship",
"company_name": "Brown University",
"country": "USA",
"start_date": "2017-01-01",
"end_date": "2017-04-30",
"skills": [
"Statistical analysis",
"User interactions",
"Crowdsourcing system"
],
"job_details": "Performed statistical analysis on user interactions for the crowdsourcing system 'Drafty' HCOMP 2017. Advisor: Jeff Huang."
},
{
"position_name": "Software Engineer Internship",
"company_name": "Google Inc.",
"country": "Japan",
"start_date": "2016-09-01",
"end_date": "2016-12-31",
"skills": [
"Android",
"Chrome",
"WebView",
"Language locales",
"Han character unification"
],
"job_details": "Created support for multiple language locales in Android Chrome and WebView. Fixed Han character unification in Android Nougat. Made locales consistent across all Chrome supported Android Versions."
},
{
"position_name": "Summer Trainee Engineering Program Internship",
"company_name": "Google Inc.",
"country": "Japan",
"start_date": "2015-05-01",
"end_date": "2015-09-30",
"skills": [
"Bug assignment system",
"Google's internal bug organizer"
],
"job_details": "Improved the bug assignment system in Google’s internal bug organizer."
}
],
"education_qualifications": [
{
"school_name": "The University of Edinburgh, School of Informatics",
"school_type": "University or equivalent",
"degree_type": "Master's Degree or equivalent",
"faculty_department": "",
"specialization_subjects": "Artificial Intelligence",
"country": "United Kingdom",
"start_date": "2017-09-01",
"end_date": "2018-11-30",
"learning_mode": "In-person learning",
"education_details": "Master of Science with Distinction in Artificial Intelligence."
},
{
"school_name": "University of Toronto, Faculty of Arts and Sciences",
"school_type": "University or equivalent",
"degree_type": "Bachelor's Degree or equivalent",
"faculty_department": "",
"specialization_subjects": "Computer Science and Mathematics",
"country": "Canada",
"start_date": "2012-08-01",
"end_date": "2016-06-30",
"learning_mode": "In-person learning",
"education_details": "Honors Bachelor of Science with Distinction in Computer Science and Mathematics."
},
{
"school_name": "Waseda University, School of Fundamental Science and Engineering",
"school_type": "University or equivalent",
"degree_type": "N/A",
"faculty_department": "",
"specialization_subjects": "",
"country": "Japan",
"start_date": "2014-08-01",
"end_date": "2015-07-31",
"learning_mode": "In-person learning",
"education_details": "One year Exchange Program (University of Toronto)."
}
]
}
}
}
}
Valid Attribute Values within education_qualifications
learning_mode
The only possible values for the learning_mode attribute within the education_qualifications list are as follows. These values will always be in English:
In-person learning
Online/remote learning
Hybrid
Trainee programme
degree_type
The only possible values for the degree_type attribute within the education_qualifications list are as follows. These values will always be in English:
Doctorate/PhD or equivalent
Master’s Degree or equivalent
Bachelor’s Degree or equivalent, Diploma or equivalent
High School/Secondary School Diploma or equivalent
Professional Certificate or equivalent
N/A
Related topics: AI Resume parsing, scrape CV, AI resume scraper, AI resume parser, Parse PDF resume API, Free Resume Parsing API, Parse PDF resume API