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 .

Robotics Controls Engineer

Terranova · Berkeley

Company Description

Backed by leading climate and American dynamism investors, Terranova builds intelligent robotic systems to terraform the Earth itself - lifting land, restoring wetlands, and protecting critical infrastructure from floods and sea-level rise.

Our mission is to preserve the built environment, create new habitats, and usher in an era of abundance. Our work supports climate resilience, disaster recovery, and defense across the United States and beyond.

We’re assembling a world-class team that wants to work on something real, physical, and civilization-scale. If you want your work to reshape the world (literally), this is the place to do it.

What to to Expect

We’re seeking a robot controls and machine learning specialist to develop algorithms that give our robotic systems adaptive, intelligent behavior. You’ll design and tune controllers, build dynamic models, and integrate them with perception and sensor data. This is a chance to bridge classical control with modern machine learning to shape how machines move through the Earth.

Key Responsibilities

  • Develop and tune controllers (PID, MPC, optimal/robust control) for dynamic, nonlinear systems.

  • Build and validate physical models for simulation, hardware-in-the-loop testing, and autonomy.

  • Train and deploy ML models for perception, planning, or adaptive control (supervised or RL).

  • Integrate algorithms with firmware and cloud teams, ensuring real-time safety and stability.

  • Profile, optimize, and verify performance under latency, jitter, and compute constraints

  • Comfortable with the pace and intensity of early-stage startup life, including long days, 6-day workweeks, and extended field hours

  • Bachelor’s degree or higher in Computer Science or related field

  • U.S. permanent residency required

Preferred Skills and Experience

  • Python/C++ with PyTorch/JAX

  • MPC/OSQP/CasADi

  • EKF/UKF/factor graphs

  • System ID, RL (PPO/SAC) with safety shields

  • ROS2, ONNX/TensorRT

  • Latency and jitter profiling

  • PCB and embedded systems design skills are a huge bonus

Ideal Archetype

  • Have worked on large complex robotic systems - various sensors, multiple motors/robots, reinforcement learning based on robot data

  • Maker background - love building stuff, work is fun to you

  • Coming from a startup environment - high ownership, fast paced environment

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