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 .

Full Stack Engineer

Navierai · San Francisco

About Navier AI

Navier AI is building the first autonomous engineering agents. AI systems that can design, simulate, and optimize complex products to achieve breakthrough levels of performance. Our mission is to enable engineers to move beyond today’s slow, manual design cycles by providing agents that reason about physics, explore design trade-offs, and generate high-performance solutions across aerospace, automotive, and advanced manufacturing.

We’re backed by top-tier investors and work directly with industry leaders to deploy AI-native tools that go far beyond today’s design automation.

Role Overview

We’re hiring a Full Stack Engineer to build the interactive interfaces and backend services that power our autonomous engineering agents. You’ll be responsible for creating seamless user experiences that let engineers visualize complex geometry, interact with AI agents, and manage design workflows—all while collaborating closely with ML, backend, and simulation teams.

Responsibilities

  • Build interactive web applications using TypeScript, React, and Three.js to visualize CAD models, simulation results, and agent outputs
  • Develop backend services in Python to power workflows, handle model inference requests, and manage user data
  • Design intuitive UIs and workflows that make AI-powered engineering agents accessible and useful to domain experts
  • Implement real-time rendering and 3D visualization pipelines for CAD, meshes, and simulation outputs
  • Collaborate with ML and backend engineers to connect front-end tools with AI models and simulation infrastructure
  • Ensure application performance and scalability through robust state management, API design, and efficient data handling
  • Participate in architecture discussions and help define best practices for frontend + backend integration
  • Own features end-to-end, from design to deployment, in a fast-paced startup environment

 

Qualifications

Required

  • Strong proficiency in TypeScript and React
  • Experience building 3D interactive experiences with Three.js or similar frameworks
  • Solid backend development experience in Python (FastAPI, Flask, or Django preferred)
  • Familiarity with API design, authentication, and data handling best practices
  • Ability to work across the stack and own features from frontend to backend
  • Comfort working with scientific/engineering data formats (e.g., meshes, STL, point clouds)
  • Strong product intuition and ability to collaborate closely with designers and engineers

Bonus

  • Experience with CAD visualization, computational geometry, or simulation tools
  • Knowledge of WebGL or shader programming (GLSL, WGSL)
  • Experience integrating ML model inference into production apps
  • Familiarity with containerization (Docker) and cloud deployment (AWS, GCP, or Azure)
  • Prior work in engineering-focused or scientific software companies

Why This Role Matters

The interfaces you build will be the primary way engineers interact with Navier’s autonomous agents. You’ll shape how complex geometry, simulation results, and AI-driven design decisions are visualized and explored. Your work will directly impact the usability, adoption, and trustworthiness of a category-defining product.

What We Offer

  • Competitive compensation, including salary and equity
  • Direct exposure to high-impact technical problems in aerospace, automotive, and advanced manufacturing
  • Opportunity to help define a new category of engineering software