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 .

AI Infrastructure Engineer

Intercom · Dublin, Ireland

Intercom is the AI Customer Service company on a mission to help businesses provide incredible customer experiences. 

Our AI agent Fin, the most advanced customer service AI agent on the market, lets businesses deliver always-on, impeccable customer service and ultimately transform their customer experiences for the better. Fin can also be combined with our Helpdesk to become a complete solution called the Intercom Customer Service Suite, which provides AI enhanced support for the more complex or high touch queries that require a human agent. 

Founded in 2011 and trusted by nearly 30,000 global businesses, Intercom is setting the new standard for customer service. Driven by our core values, we push boundaries, build with speed and intensity, and consistently deliver incredible value to our customers.

What's the opportunity?

We’re looking for Senior+ AI Infrastructure Engineers to build the systems that train and serve Intercom’s next generation of AI products.

Intercom is an AI company that builds from the GPU all the way up to a user agent that resolves millions of customer service queries a month. 

You’ll join a small, highly technical team working at the cutting edge of modern AI infrastructure. The AI Infra team built the training pipelines and runs the inference for custom models like Fin Apex, which outperforms frontier models in customer service tasks, and is the foundation of the AI Group's full stack approach to AI.

We’re particularly interested in engineers who have:

  • A track record of working on model training or model inference at scale, or on low‑level GPU coding (e.g. CUDA, Triton). Experience with one is great, multiple is even better.

What will I be doing?

As a Senior AI Infrastructure Engineer focused on model training and inference, you will:

  • Implement and scale training pipelines for large transformer and LLM models, from data ingestion and preprocessing through distributed training and evaluation.
  • Build and optimize inference services that deliver low‑latency, high‑reliability experiences for our customers, including autoscaling, routing, and fallbacks.
  • Work on GPU‑level performance: tuning kernels, improving utilization, and identifying bottlenecks across our training and inference stack.
  • Collaborate closely with ML scientists to implement cutting edge training and inference methods and bring them to production.
  • Play an active role in hiring, mentoring, and developing other engineers on the team.
  • Raise the bar for technical standards, reliability, and operational excellence across Intercom’s AI platform.

Profile we’re looking for:

These are indicative, not hard requirements

We’re looking to hire Senior+ AI Infrastructure Engineers. You’re likely a great fit if:

  • You have 5+ years of experience in software engineering, with a strong track record of shipping high‑quality products or platforms.
  • You hold a degree in Computer Science, Computer Engineering, or a related field (or you have equivalent experience with very strong fundamentals).
  • You have hands‑on experience with one or more of the following:
    • Model training (especially transformers and LLMs).
    • Model inference at scale (again, especially transformers and LLMs).
    • Low‑level GPU work, such as writing CUDA or Triton kernels.
  • Comfortable working in production environments at meaningful scale (traffic, data, or organizational).
  • You communicate clearly, can explain complex technical topics to different audiences, and enjoy close collaboration with both engineers and non‑engineers.
  • You take pride in strong technical fundamentals, love learning, and are willing to invest in your own development.
  • Have deep knowledge of at least one programming language (for example Python, Ruby, Java, Go, etc.). Specific language experience is less important than your ability to write clean, reliable code and learn new stacks quickly.

Bonus skills & attributes

None of these are required, but they’re nice to have:

  • Experience at AI native companies that train and/or run inference for their own models (e.g. modern AI labs or AI‑native product companies).
  • Experience running training or inference workloads on Kubernetes.
  • Experience with AWS or other major cloud providers.
  • Production experience with Python in ML or infrastructure contexts.
  • Demonstrated passion for technology through personal projects, open source, meetups, or publishing content about your work and learnings

Benefits

We are a well treated bunch, with awesome benefits! If there’s something important to you that’s not on this list, talk to us! 

  • Competitive salary and equity in a fast-growing start-up
  • We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen
  • Regular compensation reviews - we reward great work!
  • Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated.
  • Pension scheme & match up to 4%
  • Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents
  • Flexible paid time off policy
  • Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones
  • If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too 
  • MacBooks are our standard, but we also offer Windows for certain roles when needed.

#LI-Hybrid

Policies 

Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

We have a radically open and accepting culture at Intercom. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our core values.  

Intercom values diversity and is committed to a policy of Equal Employment Opportunity. Intercom will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.