ATS Resume Keyword Checker.
Paste any AI or tech job description alongside your resume to instantly see your ATS keyword match score, which skills you already cover, and which gaps to close before you apply.
How it works
Paste the job description
Copy the full job posting — requirements, responsibilities, and preferred qualifications — and paste it into the left panel.
Paste your resume
Copy your resume as plain text (use "Export as plain text" in Word or Google Docs) and paste it into the right panel.
Get your match score
Click "Check ATS Match" and instantly see your score, a list of matched keywords (green) and missing ones (amber) to add.
Why ATS keywords matter for AI & tech jobs
Most large technology companies — and many mid-size AI startups — route every application through an Applicant Tracking System (ATS) before a human recruiter ever sees it. The ATS scans your resume for specific keywords and phrases that match the job description, then ranks or filters candidates accordingly.
In the AI and machine learning space this is especially pronounced: a recruiter searching for "PyTorch", "RAG", or "distributed training" will only surface resumes that contain those exact terms. Even if you have hands-on experience, a vague description like "built neural network models" may not surface your resume for a role that requires "PyTorch" and "transformer fine-tuning".
Tailoring your resume with precise, job-specific keywords — ones you genuinely possess — is one of the highest-leverage actions you can take before applying. This tool helps you spot the gaps in seconds so you can invest your time where it counts.
Frequently asked questions
Is my resume data safe?
Completely. All processing happens inside your browser using JavaScript. Your resume text and the job description are never transmitted to any server, stored in a database, or logged anywhere. You can verify this by checking your browser's network tab — no requests are made when you click "Check ATS Match".
How accurate is the keyword matching?
The checker uses a curated list of AI/ML/tech skill terms plus a standard stopword filter, and supports common multi-word phrases (e.g. "machine learning", "retrieval augmented generation", "distributed training"). It intentionally prioritises precision over recall — genuine domain keywords are weighted more heavily than generic words — so the score reflects real signal, not noise.
Should I add every missing keyword to my resume?
No. Only add keywords that accurately describe your actual experience. Padding your resume with skills you do not have will backfire in phone screens and technical interviews. Use the missing keywords list as a guide to identify genuine gaps you can address (e.g. through a project or a course) or as a reminder to describe existing experience more specifically.
What score should I aim for?
A score of 60–80 % is a solid target for a tailored application. Above 80 % usually means you are a strong fit — assuming the keywords reflect genuine experience. Below 40 % suggests either the role is a poor fit or your resume is using different terminology than the job description.
Does the tool support non-English resumes?
The tool is optimised for English-language job descriptions and resumes. Technical terms in AI/ML (Python, PyTorch, Kubernetes, etc.) are usually written in English even in non-English resumes, so those will still be matched correctly.
How often should I run this check?
Ideally once per application. Each job description uses slightly different language, so a resume tuned for one posting may score poorly on another. A few targeted tweaks per application can meaningfully increase your interview rate.
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