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 .

Computational Imaging Engineer Intern

Metalenz · Boston, MA

The Position

Metalenz is developing next-generation sensing systems for consumer electronics with metasurface technology. As an intern on the computational imaging team, you will work on cutting-edge computational imaging systems by developing image processing algorithms that integrate optical simulations and data pipelines. A successful candidate will have strong skills in optical imaging, computational algorithms, and Python; experience with ML frameworks, data analysis, and AWS is a plus.

What You’ll Do

  • Develop and implement advanced imaging processing algorithms for computational imaging applications.

  • Build pipelines that combine optical imaging system simulations with computational imaging and machine learning.

  • Collaborate closely with ML engineers, data scientists, and optical engineers to develop optimized computational imaging systems.

  • Establish robust data quality assurance pipelines to validate and quantify data integrity.

What You'll Need

  • Currently has or is in the process of obtaining a Master's or PhD's degree in imaging science, computer science, optics, electrical engineering, or a relevant field.

  • Demonstrated experience in optical imaging principles and techniques as demonstrated through research, academic projects, or professional work.

  • Proven experience with machine learning frameworks and methodologies.

  • Solid Python coding capabilities.

Preferred Qualifications

  • Background in data analysis and data classification techniques.

  • Practical knowledge of optical systems and instrumentation.

  • Hands-on experience with Amazon Web Services (AWS) infrastructure.

The Company

Metalenz, a Boston based venture backed startup built on foundational research from Harvard University, develops next-generation imaging and sensing solutions for high volume consumer electronics markets using patented low-cost metasurface technology, advanced image processing, and novel machine learning algorithms. The Company’s latest product, Polar ID, is a groundbreaking polarizing camera that leverages the unique characteristics of metasurfaces to enable secure and affordable face unlock for all smartphones.

We are a fast-growing, dynamic company with a vibrant startup culture. Our deeply technical and creative team is dedicated to developing groundbreaking technologies that bring new ways of seeing and sensing to billions of people. We foster a workplace that values autonomy, encourages innovation, and supports career growth, giving you the opportunity to take ownership of impactful projects and grow with us.

What We Offer

  • Based in downtown Boston near TD Garden, Metalenz is conveniently located across the street from North Station.

  • Employee Assistance Program

  • Collaborative office space, flexible work schedule with hybrid and/or work-from-home arrangements for qualified positions.

  • Complimentary snacks and drinks, and occasionally lunch on-site.

  • Free gym and bike parking on-site.

  • Fun, energizing, highly collaborative environment in which each team member has the opportunity to make an impact.

The base compensation range for this position is $5,500 – $8,500 per month. Our compensation ranges are determined by role and experience level. The range reflects the minimum and maximum target for new hire salaries for the position in the noted geographic area. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training.

Metalenz is committed to a diverse and inclusive workplace. Metalenz is an equal opportunity employer and does not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We are committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let your recruiter know.

To all recruitment agencies: Metalenz does not accept agency resumes. Please do not forward resumes to our employees. Metalenz is not responsible for any fees related to unsolicited resumes.

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