Key Takeaways

  • 75% of U.S. employers use automated applicant tracking systems to screen resumes before a human reviews them (Harvard Business School & Accenture, 2021)
  • The most common ATS failures are missing keywords, incompatible formatting, and incorrect file types
  • ResumeGeni scores your resume across 8 parsing layers — modeled on the same steps enterprise ATS platforms like Workday, Greenhouse, and Taleo use to evaluate candidates

How ATS Resume Scoring Works

Applicant tracking systems parse your resume into structured data — extracting your name, contact info, work history, skills, and education — then score how well that data matches the job requirements. Many ATS rejections happen because the parser couldn't extract critical fields, not because the candidate wasn't qualified.

LayerWhat It ChecksWhy It Matters
Document extractionFile format, encoding, readabilityCorrupted or image-only PDFs fail immediately
Layout analysisTables, columns, headers, footersMulti-column layouts break field extraction
Section detectionExperience, education, skills headingsNon-standard headings cause sections to be missed
Field mappingName, email, phone, dates, titlesMissing contact info is a common cause of immediate rejection
Keyword matchingJob-specific terms, skills, certificationsKeyword overlap affects recruiter search visibility and ATS scoring
Chronology checkDate ordering, gap detectionReverse-chronological order is expected by most ATS
QuantificationMetrics, numbers, measurable outcomesQuantified achievements help human reviewers and some scoring models
Confidence scoringOverall parse quality and completenessLow-confidence parses get deprioritized in results

Frequently Asked Questions

Is ResumeGeni free?
Yes. ResumeGeni is currently in beta — ATS analysis, scoring, and initial improvement suggestions are free with no signup required. Full guidance and saved reports may require a free account.
What file formats are supported?
PDF, DOCX, DOC, TXT, RTF, ODT, and Apple Pages. PDF and DOCX are recommended for best ATS compatibility.
How is the ATS score calculated?
Your resume is processed through an 8-layer parsing pipeline that extracts structured data the same way enterprise ATS platforms do. The score reflects how completely and accurately your resume can be parsed, plus how well your content matches common ATS ranking criteria.
Can ATS read PDF resumes?
Yes, but not all PDFs are equal. Text-based PDFs parse well. Image-only PDFs (scanned documents) and PDFs with complex tables or multi-column layouts often fail ATS parsing. Our analyzer will flag these issues.
How do I improve my ATS score?
Focus on three areas: use a clean single-column format, include keywords from the job description naturally in your experience bullets, and ensure all sections (contact, experience, education, skills) use standard headings.

ATS Guides & Resources

Built by engineers with 12 years of experience building enterprise hiring technology at ZipRecruiter. Last updated .

Senior, ML Engineer - Offline Perception

Torcrobotics · Remote - US, Ann Arbor, MI

About the Company 

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. 
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. 
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer. 

Meet The Team:  

Pseudo-Labeling team's goal is to create high quality annotations on sensor data (images, point clouds). The annotations include 2D, 3D bounding boxes, classes, trajectories, lane lines, segmentations, depths etc. The annotations are then used by different downstream users, for example, perception teams use it to train various models and simulation teams use it for generating new data. 

What You’ll Do:  

  • Design, implement, test and deploy offline object detection, tracking and fusion modules to automatically create annotations on Cloud Services from logged sensor data (Cameras, Lidars, Radars)
  • Demonstrated project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution. 
  • Stay up to date with the latest developments in AI and ML for autonomous driving.
  • Independently develop offline perception models or algorithms using disciplined software development processes, making recommendations for developing new code or re-using existing code, implementing version control, and maintaining 
  • Documentation of created applications. 
  • Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics models and workflows. 
  • Proactively assess current capabilities to identify areas for improvement proposing solutions that align with core strategy and operation. 
  • Measure and track auto labeling quality to meet internal customer requirements.
  • Guide and produce information products, supporting visualization and data accessibility in a customer-centric manner. 
  • Evaluate and make recommendations regarding technical advances that improve productivity and quality, reduce flow times, and enhance operational surety. 
  • Develop guidelines and standards for analytics and machine learning models, their deployment, and associated processes.  
  • Provides technical guidance or business process expertise, technical leadership, coaching and mentoring to team members.  

What You’ll Need to Succeed:  

  • Considered highly skilled and proficient in discipline; conducts complex, important work under minimal supervision and with wide latitude for independent judgment. 
  • Scope of Influence: Expected to drive alignment across team interfaces to the rest of the organization. Designs, maintains and owns team technical solutions and drives consensus.  Mentors and guides engineers within the group.  
  • Bachelor’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 6+ years of experience OR;  
  • Master’s Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 3+ years of experience OR; 
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