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 .

Research Engineer

Chaidiscovery · San Francisco office

About Chai Discovery

Chai is a research lab working on AI to unlock biology. Our models design new molecules for new medicines. We are changing how biologists develop drugs, just as Anthropic is changing how engineers write code. Our vision is a design suite for molecules, with applications across life sciences, agriculture, materials and beyond.

Our founders have been at the forefront of this field from the beginning. We are backed by Thrive, General Catalyst, OpenAI, Dimension and other tier-one investors. We partner with global life sciences companies like Eli Lilly on deals that are transforming industry.

We are known for talent density, rigorous research and pace of execution.

About the role

We are seeking an AI Research Engineer to help design, train, evaluate, and optimize Chai’s core models and infrastructure, working in tight loops with research scientists. Chai's models are moving beyond protein structure prediction into real-world therapeutic engineering. This is a chance to push the frontier of AI drug design, working alongside a craft-obsessed team of micro-pessimists and macro-optimists.

  • Develop and optimize all the infrastructure & tooling upon which our AI research depends.

  • Collaborate with AI researchers to understand, implement and optimize new research directions.

  • Integrate AI models into production systems, ensuring scalability and reliability.

About you

Ideal backgrounds include high-performance computing, custom CUDA kernels and GPU programming, AI/ML + data systems at scale.

  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.

  • Strong proficiency in programming languages such as Python and deep learning frameworks like PyTorch.

  • Deep understanding of operating system internals.

  • Experience with HPC infrastructure such as Slurm and Kubernetes.

  • Experience with performance engineering and profiling for CPU and CPU workloads.

  • Experience writing, building, and maintaining large-scale ETL pipelines.

We offer

The opportunity to work at the frontier of AI, with world-class people, on a mission that matters. We protect & promote a culture of high velocity and ownership. We offer highly competitive compensation.