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 Rust Engineer

Appodeal · Barcelona, Spain

Appodeal is a dynamic US-based product company with a truly global presence.

We have offices in Warsaw, Barcelona and Parkland (FL), along with remote team members located around the world.

Our company thrives on diversity, collaboration, and innovation, making us a leader in the mobile app monetization space.

Why Appodeal?

At Appodeal, we’re more than just a company—we’re a team united by a common mission: Help people discover and grow their talents through products that enable successful mobile app businesses!

We take pride in our cutting-edge product and our internationally dispersed team of talented professionals.

Here’s what we value, and what we hope you do too:

  • Continuous Learning and Growth: We are passionate about learning, growing personally, and building rewarding careers.
  • Making an Impact: We are committed to building a history-defining company that leaves a lasting impact on the mobile app industry.
  • Solving Exciting Challenges: We tackle complex problems every day, supported by a team of world-class professionals and mentors.
  • Enjoying the Journey: We believe in having fun while working toward our goals.

About Appodeal

Appodeal is a dynamic US-based product company with a truly global presence.

We have offices in Warsaw, Barcelona, and Parkland (FL), along with remote team members located around the world.

Our company thrives on diversity, collaboration, and innovation, making us a leader in the mobile app monetization space.


Why Appodeal?

At Appodeal, we’re more than just a company—we’re a team united by a common mission:
Help people discover and grow their talents through products that enable successful mobile app businesses.

We take pride in our cutting-edge product and our internationally distributed team of talented professionals.

Here’s what we value:

  • Continuous Learning and Growth – We invest in development and long-term careers
  • Making an Impact – We are building a history-defining company in the mobile industry
  • Solving Exciting Challenges – Complex, large-scale problems are part of our daily work
  • Enjoying the Journey – We believe great results come with a positive environment

About the Role

We are looking for a Senior Rust Engineer to join our Barcelona team and contribute to building high-performance, real-time systems powering our ML-driven AdTech platform (Mobile Growth Platform).

In this role, you will work on core backend infrastructure and ML platform components, focusing on low-latency, high-load services that process large-scale traffic in real time.

You will play a key role in developing and optimizing systems such as real-time applications, feature stores, user identity services, and custom inference layers, ensuring scalability, reliability, and performance.


Responsibilities

  • Contribute to the development of real-time applications and ML platform components
  • Build and maintain high-load, low-latency backend services
  • Work on in-house solutions including:
    • Feature stores
    • User identity services
    • Custom inference layer
    • ML platform infrastructure
  • Optimize system performance across on-premise Docker & Kubernetes environments
  • Design and implement solutions for traffic scaling and system reliability
  • Collaborate with ML, data, and engineering teams to support production ML systems
  • Continuously improve system architecture, observability, and efficiency

Tech Stack

  • Languages: Rust, Python
  • Data & Streaming: Kafka, SQL, Redis, ScyllaDB, Delta Lake, Databricks
  • Infrastructure: Docker, Kubernetes (on-premise)
  • Tools: GitHub

Requirements

  • 5+ years of experience in software engineering
  • Strong proficiency in Rust
    or
    proficiency in C/C++/Zig with willingness to transition to Rust
  • Experience designing and building high-load, performance-critical systems
  • Solid understanding of system design, concurrency, and performance optimization
  • Basic knowledge of machine learning workflows and tools

Nice to Have

  • System programming experience (C, C++, Zig)
  • Experience in ML engineering / MLOps
  • Strong Python skills
  • Familiarity with AdTech standards (OpenRTB, MRAID, VAST)
  • Experience with WASM / WASI
  • Background in distributed systems and real-time processing
  • Location: Barcelona, Spain (office attendance 4 days per week)

What We’re Looking For

  • Autonomous and self-driven engineer with strong ownership mindset
  • Passion for engineering excellence, performance, and scalability
  • Interest in