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 .

Large Model Algorithm Researcher

Tencent · Singapore-CapitaSky

Business Unit

Technology Engineering Group (TEG) is responsible for supporting the company and its business groups on technology and operational platforms, as well as the construction and operation of R&D management and data centers, TEG provides users with a full range of customer services. As the operator of the largest networking, devices, and data center in Asia,TEG also leads the Tencent Technology Committee in strengthening infrastructure R&D through internal and distributed open source collaboration, constructing new platforms and supporting business innovation.

What the Role Entails

1. Responsible for the core technology development in the Post-Training phase of large language models, building and optimizing a high-quality Reward System. Continuously enhance the model's capabilities in complex instruction adherence, logical reasoning, and value alignment through Reward Modeling (RM) and Reinforcement Learning (RL) algorithms.
2. Conduct in-depth research and optimization of post-training algorithms such as RLHF to improve model training stability and final outcomes.
3.Manage and synthesize data in the post-training phase, design an efficient data feedback loop mechanism, utilize techniques like SFT and Self-Instruct to generate high-quality training data, and establish a closed-loop signal modeling system from User Feedback to model iteration. 4. Perform comprehensive evaluation and analysis of post-training models, develop scientific evaluation metrics, and keep up with cutting-edge technology trends, quickly translating the latest research results into business value.

Who We Look For

1.Master's degree or higher in Computer Science, Software Engineering, Artificial Intelligence, or related fields.
2.Deep understanding of the Transformer architecture and the principles of large language model training, with substantial research and practical experience in one of the post-training areas such as LLM Alignment, RLHF, or Reward Modeling.
3. Solid foundation in algorithms and engineering implementation capabilities, proficient in Python, and familiar with deep learning frameworks such as PyTorch or TensorFlow.
4. Practical experience in distributed training, familiar with large-scale training and inference frameworks like Megatron-LM, DeepSpeed, and vLLM. Experience in training or tuning models with billions or hundreds of billions of parameters is preferred.
5. Excellent research skills, with a record of high-quality publications (NeurIPS, ICLR, ICML, ACL, EMNLP, etc.) or contributions to high-impact projects in the open-source community (e.g., HuggingFace) preferred.
6. Strong technical enthusiasm and self-motivation, adept at analyzing and solving complex problems, with good teamwork and communication skills.

Equal Employment Opportunity at Tencent

As an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.

View full listing