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 .

Forward Deployed Engineer (Rust)

Spiceai · Bellevue, Washington

Building data-driven AI applications and agents is too complex, even for advanced developers.

This new generation of applications need fast, secure access to data across disparate systems, the ability to search and reason over that data, and infrastructure that’s reliable enough to run in production. Today, teams often need to piece together query engines, search systems, caches, and AI tooling, adding significant complexity along the way.

At Spice AI, we simplify this by unifying query federation, search, and AI into a single runtime for building intelligent applications. Our mission is to make building AI-powered software as easy building a modern web application and help developers build the next generation of applications. We offer both open source and fully managed cloud deployments.

For a deeper dive into the vision, watch Founder and CEO Luke Kim's CMU Databases talk on Spice.ai OSS at https://www.youtube.com/watch?v=tyM-ec1lKfU and read his Materialized View interview at https://materializedview.io/p/building-a-cdn-for-databases-spice-ai.

At Spice AI, we hire for MEI: Merit, Excellence, and Intelligence. We're looking for exceptional, ambitious builders who are driven to solve hard problems and push the boundaries of what's possible for AI.

This role requires a Forward Deployed Engineer to embed with customers and partners, accelerating adoption through direct engineering contributions. Responsibilities include deploying, optimizing, and extending Spice.ai solutions in production environments, while collaborating on product improvements.
 
If open source, distributed systems, and real-world search & AI deployment drive you, apply.
This role requires a Forward Deployed Engineer to embed with customers and partners, accelerating adoption through direct engineering contributions. Responsibilities include deploying, optimizing, and extending Spice.ai solutions in production environments, while collaborating on product improvements.
 
If open source, distributed systems, and real-world search & AI deployment drive you, apply.
About Spice AI

Founded in June 2021 by Microsoft and GitHub alumni Luke Kim and Phillip LeBlanc, Spice AI creates technology to help developers build intelligent applications and agents that learn and adapt.

Before co-founding Spice AI, Luke was the co-creator of Azure Incubations in the Office of the Azure CTO, where he led cross-functional engineering teams to create and develop technologies including Dapr and OAM.

Spice AI is backed by some of the top industry angel investors and leaders, including Nat Friedman, Mark Russinovich, CTO of Microsoft Azure, and Thomas Dohmke, CEO of GitHub, who is also on the board.

Spice AI also has notable VC backing from Madrona Venture Group, Basis Set Ventures, Founders' Co-op, and Picus Capital.

Learn more:

- On TechCrunch and GeekWire
- About the team at spice.ai/careers
- The Spice.ai general availability announcement blog post
- The Spice.ai OSS project announcement blog post

Who We Are Looking For

  • An exceptional engineer.
  • A problem solver who starts with customer problems and solves them with technology.
  • A thinker who challenges the status quo, rejects the current world model, and builds better for everyone.
  • A positive force who asks what's possible instead of focusing on limitations.
  • Someone who views work as meaningful, not just a job.
  • Comfortable with ambiguity and unknowns, leading by creating clarity.
  • Passionate about high performance with high standards.
  • What We're Looking For

  • 5+ years in engineering roles, with focus on deploying data, search, and AI systems in enterprise environments.
  • Experience designing, implementing, and scaling production database engines, distributed systems, search engines, and data & AI pipelines.
  • Track record of strong design, architectural, engineering, and product decisions in customer-facing contexts.
  • Excellent communication skills.
  • Ability to ramp up quickly and deliver impact.
  • Contributions to open-source projects preferred.
  • Experience with Apache infrastructure, CNCF stack, or cloud-native development.
  • Deep knowledge of databases, data warehousing, data lakes, search, virtualization, and mesh principles.
  • Proficiency with Databricks, Snowflake, Starburst, Dremio, ElasticSearch, or similar.
  • Strong SQL skills in queries, syntax, modeling, and optimizations.
  • Familiarity with data storage like HDFS, Amazon S3, and relational databases.
  • Skills in data integration, including ETL/ELT, ingestion, and transformation.
  • Ability to tune performance and optimize systems.
  • Knowledge of data security, privacy, authentication, authorization, and encryption.
  • Problem-solving for complex data challenges.
  • Presentation skills for technical and executive audiences.
  • Ability to explain concepts to technical and non-technical stakeholders.
  • Relationship-building with customers and partners.
  • Willingness to travel 20%+ based on customer needs.
  • In This Role, You'll

  • Embed with enterprise customers and partners to deploy Spice.ai OSS/Enterprise and Cloud Platform in production.
  • Build, configure, and optimize proof-of-concepts and deployments for performance, scalability, and security.
  • Collaborate with engineering to incorporate customer feedback into core product features.
  • Resolve technical blockers, debug issues, and extend Spice.ai capabilities on-site or remotely.
  • Design end-to-end architectures using Spice.ai for data querying, search, and AI inference.
  • Identify expansion opportunities and drive adoption of new features.
  • Work side-by-side with founders as a leader in customer success engineering.
  • Contribute to Spice.ai OSS improvements based on real-world usage.
  • Own initiatives to refine offerings and deliver superior developer experiences.
  • Your First 90 Days

  • First week: Deploy a Spice.ai instance for a customer scenario and fix a deployment issue.
  • First month: Ramp up, lead a POC deployment, and contribute optimizations to Spice.ai OSS.
  • 30-60 days: Take ownership of a customer deployment area, from architecture to production rollout.
  • 60-90 days: Propose and execute a technical strategy for scaling customer integrations.