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 .

DSP & Measurement Engine Engineer

Qualinx · Delft

Join our cutting-edge start-up adventure!

Who are we?

Join the Revolution in GNSS and IoT Connectivity

At Qualinx, we’re not just building chips, we’re engineering the future fabric of the connected world. As a pioneering semiconductor scale-up, we’re transforming how devices connect, communicate, and operate through our ground-breaking Digital RF technology. Our mission goes beyond ultra-low power GNSS: we’re redefining what’s possible in adaptive, scalable, and intelligent connectivity for the Internet of Things.

Born from deep-tech innovation at TU Delft, our team of visionary engineers and bold thinkers is tackling the toughest challenges in GNSS and IoT, starting with power consumption and expanding into dynamic, context-aware solutions that adapt to any environment or use case. We’ve already achieved what many thought impossible: the world’s most advanced GNSS chipset. But that’s just the beginning.

At Qualinx, we believe that the future of connectivity lies in precision, efficiency, and adaptability. Our ambition is to become the invisible thread that seamlessly interconnects billions of devices: powering a smarter, more responsive world.

What Sets Us Apart

Joining Qualinx is about becoming part of a culture that’s as ambitious as it is authentic. We hold ourselves to high standards, thrive on solving the unexpected, and push boundaries together. But we also know how to enjoy the ride. Our culture is a unique blend of curiosity, team spirit, and a touch of unconventional charm. It’s fast-paced, fun, and grounded in a sober sense of purpose and perspective. Whether we’re deep in design reviews or sharing laughs over lunch, we’re building something meaningful together. At Qualinx, you’re not just contributing to a ground-breaking technology, you’re helping shape a team that’s redefining what it means to work in deep tech.

Job Description 

  • Design and optimize algorithms for GNSS acquisition, tracking, and measurement engines to achieve best-in-class performance.

  • Implement and validate algorithms on embedded platforms using C in real-time operating systems.

  • Develop simulation models (floating-point and fixed-point) to analyse system performance and guide design decisions.

  • Create robust software tools in MATLAB and Python for algorithm development, testing, and automation.

  • Collaborate across disciplines (ASIC, FPGA, RF, and software teams) to ensure seamless integration of algorithms into silicon-based systems.

  • Perform rigorous testing and debugging, ensuring reliability and compliance with performance targets.

  • Document and present findings clearly to internal teams and external stakeholders.

  • Contribute to continuous improvement by following and enhancing company software engineering best practices.

Job requirements

Must haves

Qualinx is looking for a result-driven and conscientious GNSS Engineer. Someone who thrives in an environment where your proactive and can-do attitude is highly appreciated. The ideal candidate for this role must have:

  • Master’s in electrical engineering (or equivalent industry experience) with 5+ years of hands-on experience and a proven track record in signal processing techniques in a relevant technology,

  • Significant knowledge of the GNSS and Communication System processing chain.

  • Embedded programming / development experience (C programming for embedded system and FPGA platform).

  • Strong Matlab/ Python and C programming skills.

  • At least 5 years of experience.

  • Good communication, reporting, and presentation skills in English.

  • Experience with GNSS acquisition and tracking algorithm implementation in real-time (chipset on embedded platform).

  • Multipath and interference mitigation techniques.

  • Experience with low-power GNSS chipset design and snapshot receiver techniques.

Nice to have

  • SDR development experience and familiarity with multi-constellation GNSS.

  • Experience mentoring other engineers for GNSS Algorithms development.

  • Experience with RF front-end integration and laboratory instrumentation for testing and validation.

  • Knowledge of wireless protocols such as Wi-Fi, Bluetooth, IoT.

  • Understanding of LEO PNT, GNSS-R