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 Platform Engineer - Performance

Weave · India

At Weave, we operate a complex distributed microservices architecture (Go, Kubernetes). As a key member of our Platform Engineering group, you will treat "Performance Testing" as an internal product. Your job is to architect the frameworks, CI/CD integrations, and self-service tooling that make performance validation invisible, automated, and easy for every developer at Weave.

  • This position will be remote, in India

  • Reports to: Engineering Manager

What You Will Own

  • Build the Internal Platform: Design and develop a scalable, self-service performance testing framework (using tools like k6 or Locust) that integrates natively into our Go/Kubernetes ecosystem.

  • Engineering, Not Just Scripting: Write production-grade code (Go/Python) to abstract away infrastructure complexity. You will build the libraries and CLI tools that allow product teams to define performance tests as code.

  • CI/CD Integration: embed performance gates directly into our deployment pipelines (GitHub Actions/GitLab CI), ensuring no regression reaches production.

  • System Architecture & Observability: Partner with Principal Engineers to analyze "third-order" effects in our distributed systems. You won't just report a slow endpoint; you will help debug the interaction between the service, the database, and the mesh to find the root cause.

  • Developer Enablement: You are the Subject Matter Expert. You will create the documentation, reference implementations, and "Golden Paths" that teach our engineering organization how to fish.

What You Will Need to Accomplish the Job

  • Software Engineering First: You are a developer at heart. You have 5+ years of experience writing backend code (Go, Python, or Java) and you understand software design patterns.

  • Platform Mindset: You have experience building tools for other developers. You understand that if a tool is hard to use, it won't get adopted.

  • Performance Expertise: You know how to break a system. You have deep experience with load, stress, and scalability testing, and you understand the difference between throughput, latency, and concurrency.

  • Infrastructure Fluency: You are comfortable working with Kubernetes, Docker, and Cloud infrastructure. You understand how to right-size a pod and how to debug a crash loop.

  • Tooling: Experience with script-as-code tools (k6, Locust) is highly preferred over UI-based legacy tools (JMeter, LoadRunner).

What Will Make Us Love You

  • Modern Tooling Experience: Hands-on experience with modern, script-as-code performance testing tools, particularly k6 (preferred) or Locust. Experience building custom tooling, libraries, or frameworks around these tools to enhance developer experience is a significant plus. This demonstrates an alignment with our "test-as-code" and developer-enablement philosophy.

  • Observability Expertise: Proficiency with modern observability stacks (e.g., Prometheus, Grafana, Datadog, ELK) and extensive experience using metrics, distributed traces, and logs to correlate application performance with underlying system behavior during performance tests.

  • Go-Specific Performance Skills: Experience with Go-specific profiling and debugging tools (e.g., pprof). Familiarity with the xk6-g0 extension for writing k6 tests directly in Go would also be a plus, as it represents a unique and powerful intersection of the exact skills required for this role: deep Go expertise combined with a modern approach to performance engineering.

  • Internal Platform Development: A proven track record of building internal developer tools, platforms, or frameworks that have measurably improved engineering productivity, velocity, and software quality within an organization.

Weave Tech Stack Familiarity: Direct experience testing Go-based microservices environments and systems utilizing Kafka, NSQ, Postgres, and/or gRPC.

At Weave, we use Artificial Intelligence (AI) tools to help us work more efficiently and create a smoother candidate experience. AI may assist with things like writing job descriptions, scheduling interviews, or reviewing applications against job-related criteria. For additional information, please review the External AI Policy Statement available on our Careers page.

Weave is an equal opportunity employer that is committed to fostering an inclusive workplace where all individuals are valued and supported. We welcome anyone who is hungry to learn, problem-solve and progress regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other applicable legally protected characteristics. If you have a disability or special need that requires accommodation, please let us know.

All official correspondence will occur through Weave branded email. We will never ask you to share bank account information, cash a check from us, or purchase software or equipment as part of your interview or hiring process.

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