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 .

Principal AI/ML Architect

Varomoney · San Francisco, CA

Varo is an entirely new kind of bank. All digital, mission-driven, FDIC insured and designed for the way our customers live their lives. A bank for all of us.

About the role
 

Join Varo Bank as a Principal AI/ML Architect and help us redefine the future of digital banking. This is a "builder-leader" role designed for someone who thrives in a fast-paced, high-growth environment. You won't just draw diagrams; you will engineer the intelligent systems that power our lending infrastructure. We are looking for a "technical hybrid" who thrives on autonomy and innovation. You will act as a key thought leader, partnering with the Senior Director of Data and AI/ML Engineering to drive Varo toward becoming an AI-first organization. Whether you are designing our future-state Feature Store using Databricks or deploying GenAI "summary bots" for our call centers, your work will directly influence the financial lives of millions of users.

Reporting directly to the Head of Data Engineering and Analytics, you will serve as the technical North Star for our AI evolution. You will leverage the full AWS GenAI stack—from Bedrock and AgentCore to complex RAG architectures—to turn Varo into a GenAI-native powerhouse. If you enjoy moving at start-up speed with the resources of a licensed bank, this is your seat.

About the role
 

Join Varo Bank as a Principal AI/ML Architect and help us redefine the future of digital banking. This is a "builder-leader" role designed for someone who thrives in a fast-paced, high-growth environment. You won't just draw diagrams; you will engineer the intelligent systems that power our lending infrastructure. We are looking for a "technical hybrid" who thrives on autonomy and innovation. You will act as a key thought leader, partnering with the Senior Director of Data and AI/ML Engineering to drive Varo toward becoming an AI-first organization. Whether you are designing our future-state Feature Store using Databricks or deploying GenAI "summary bots" for our call centers, your work will directly influence the financial lives of millions of users.

Reporting directly to the Head of Data Engineering and Analytics, you will serve as the technical North Star for our AI evolution. You will leverage the full AWS GenAI stack—from Bedrock and AgentCore to complex RAG architectures—to turn Varo into a GenAI-native powerhouse. If you enjoy moving at start-up speed with the resources of a licensed bank, this is your seat.

We recognize not everyone will have all of these requirements. If you meet most of the criteria above and you’re excited about the opportunity and willing to learn, we’d love to hear from you!

About Varo
Varo launched in 2017 with the vision to bring the best of fintech into the regulated banking system. We’re a new kind of bank – all-digital, mission-driven, FDIC-insured, and designed around the modern American consumer. 

As the first consumer fintech to be granted a national bank charter in 2020, we make financial inclusion and opportunity for all a reality by empowering everyone with the products, insights, and support they need to get ahead. Through our core product offerings and suite of customer-first features, we aim to address a broad range of consumer needs while profitably serving underserved communities that have been historically excluded from the traditional financial system.

Learn more about Varo by following us:
Facebook - https://www.facebook.com/varomoney
Instagram - www.instagram.com/varobank
LinkedIn - https://www.linkedin.com/company/varobank

Varo is an equal opportunity employer. Varo embraces diversity and we are committed to building teams that represent a variety of backgrounds, perspectives, and skills. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Beware of fraudulent job postings!
Varo will never ask for payment to process documents, refer you to a third party to process applications or visas, or ask you to pay costs. Never send money to anyone suggesting they can provide work with Varo.  If you suspect you have received a phony offer, please e-mail [email protected] with the pertinent information and contact information.

CCPA Notice at Collection for California Employees and Applicants:
https://www.varomoney.com/privacy-legal/

What you'll be doing

  • Architecting GenAI Ecosystems: Design and implement production-grade GenAI agents using AWS Bedrock, AgentCore, and Strands Agents. Build robust RAG (Retrieval-Augmented Generation) pipelines utilizing OpenSearch and S3 Vector stores.
  • Scale Modern MLOps & Feature Stores: Lead the development and integration of a world-class MLOp s platform. Build and maintain Varo's Feature Store Platform architecture and ensure low-latency data availability for both real-time lending decisions and batch model training.
  • Data Fabric & Integration: Oversee the integration of core AWS analytics services (Glue, Glue Data Catalog, Athena) to ensure AI models have high-quality, governed data "fuel."
  • High-Velocity Execution: Navigate the complexities of a fast-changing environment, collaborating across Data Science, Credit, and Product teams to move from PoC to production in weeks, not months.
  • Executive Influencing: Act as a key contributor to the Architecture Guild, using strong presentation skills to translate complex EKS/EC2 infrastructure and AI scaling strategies for executive stakeholders.
  • Drive Strategy: Serve as a subject matter expert within the Architecture Guild, presenting technical proposals and influencing senior leadership on emerging AI trends.
  • Collaborate Horizontally: Partner across domains including Data Science, Credit Policy, and Data Engineering to ensure technical alignment with business goals.
  • You'll bring the following required skills and experiences

  • Deep Experience: Ideally 10+ years in technical architecture with at least 5–7 years specifically focused on Machine Learning.
  • Architectural Foundation: Strong mastery of foundational architecture, with proven experience building agents, context stores, and vector stores.
  • AWS Mastery: Deep, hands-on experience with AWS SageMaker AI, Bedrock, S3, and OpenSearch. Familiarity with AgentCore and Strands Agents for autonomous task execution.
  • Infrastructure & Compute: Proficiency in managing server infrastructure for AI workloads, specifically Amazon EKS (Kubernetes) and EC2 optimization for model hosting.
  • Data Engineering Foundation: Expert knowledge of the AWS data stack: AWS Glue for ETL, Glue Data Catalog for metadata management, and Athena for serverless querying.
  • Certifications: AWS Certified Solutions Architect – Professional or AWS Certified Machine Learning – Specialty is highly preferred
  • The "Bridge" Mindset: A unique ability to balance high-level strategic thought leadership with a passion for hands-on, tactical execution.