Resume/CV Parsing
Parses a resume file (DOC, DOCX, TXT, RTF, PDF, JPG, JPEG, JPE, PNG, TIFF, TIF) and returns detailed data points.
Effortlessly scrape CVs and extract comprehensive candidate data with our advanced AI resume scraper. Simply upload a document, and our Parse PDF Resume API will return detailed candidate information to streamline your hiring workflow.
Supported resume files - 11 file formats:
DOC, DOCX, TXT, RTF, PDF, JPG, JPEG, JPE, PNG, TIFF, TIF
And yes - it handles those flattened PDFs where the entire resume is just images instead of text.
This endpoint is essential for extracting detailed information from resumes, and supporting various HR and recruitment applications. It also detects and processes images embedded inside PDF files (scanned documents, photos, etc.).
This API is ideal for developers building HR platforms, recruitment software, or applicant tracking systems. It automates the extraction of relevant data from resumes, ensuring accuracy and efficiency in candidate processing. Use cases include resume data extraction for applicant tracking systems, automated candidate profiling, and enhanced recruitment workflows.
The file has to be uploaded as form-data parameter called file.
An optional language parameter can also be provided (English value is set as the default one) .
AI jobs involve two key steps:
- Submitting the AI job: Initiating the process by sending the job request.
- Monitoring and receiving results: Continuously checking the job status and obtaining the final output upon successful completion.
Related SDKs/Libraries
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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 learningOnline/remote learningHybridTrainee 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 equivalentMaster’s Degree or equivalentBachelor’s Degree or equivalent, Diploma or equivalentHigh School/Secondary School Diploma or equivalentProfessional Certificate or equivalentN/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