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 .

Researcher, Model Architecture (UK)

Cartesia · London

About Cartesia

Our mission is to build the next generation of AI: ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text—1B text tokens, 10B audio tokens and 1T video tokens—let alone do this on-device.

We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.

We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.

About the Role

We’re opening our first ever office in Europe, and looking to hire incredible talent in London to advance our mission of building real-time multimodal intelligence.

Your Impact

  • Conduct groundbreaking research in neural network architecture design to advance the state-of-the-art (SOTA) in alternative architectures (e.g., state space models, efficient Transformers, hybrid architectures).

  • Design novel architectures that improve model quality, inference efficiency, and adaptability across diverse deployment environments, from cloud to on-device.

  • Explore and develop capabilities such as statefulness, long-range memory, and innovative conditioning mechanisms for enhancing model expressiveness and generalization.

  • Investigate how architectural decisions impact model trade-offs, including scalability, robustness, latency, and energy efficiency.

  • Develop new frameworks and tools to evaluate architectural innovations, benchmarking performance across research and production settings.

  • Collaborate with cross-functional teams to translate architectural research into scalable and impactful systems for real-world applications.

What You Bring

  • Deep expertise in architecture design, with experience in researching or deploying advanced architectures (e.g., state space models, transformers, RNN variants, CNN variants).

  • Strong understanding of how architectures interact with system constraints, including deployment in cloud environments or on-device.

  • Proficiency in designing architectures that balance quality, efficiency, and adaptability across different use cases and modalities (e.g., vision, audio, text).

  • Familiarity with generative modeling paradigms like autoregressive and diffusion models, and designing capabilities such as statefulness and conditioning in deep learning models.

  • A proven research track record in top-tier ML/AI venues (e.g., NeurIPS, ICML, ICLR, CVPR) or demonstrable contributions to state-of-the-art architectures.

  • Exceptional analytical and problem-solving skills, with a focus on experimentation and iterative refinement.

  • Strong programming skills in deep learning frameworks such as PyTorch or TensorFlow, and experience with profiling tools for understanding model performance.

Nice to Have

  • Prior research or publications in state space models, efficient Transformers or other alternative architectures.

  • Research or practical experience in designing architectures for multi-modal systems.

  • Early-stage startup experience or a track record of rapid innovation in R&D environments.

What We Offer

🍽 Lunch, dinner and snacks at the office.

🏥 Fully covered medical, dental, and vision insurance for employees.

🏦 Pension Plan.

✈️ Relocation and immigration support.

🦖 Your own personal Yoshi.

Our Culture

🏢 We’re an in-person team based out of San Francisco. We love being in the office, hanging out together, and learning from each other every day.

🚢 We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don’t sacrifice quality or design along the way.

🤝 We support each other. We have an open & inclusive culture that’s focused on giving everyone the resources they need to succeed.