Every job seeker wants to know what to include in a resume, but today, we're flipping the script. Let’s talk about what not to do.
If recruiters have ghosted your resume or you’re endlessly refreshing your inbox, chances are your resume might be silently screaming: “Don’t hire me.”
This guide is your behind the scenes pass into the hiring desk: what HRs hate, what makes them roll their eyes, and what makes your application land in the rejection pile (within 6 seconds).
1. Generic Objectives That Say Nothing
“To work in a challenging environment where I can grow...”
Recruiters have read it a million times. Use this prime space to showcase measurable impact, or better yet, skip it entirely and start with a resume summary tailored to the role.
Better Alternative:
"Data analyst with 3+ years of experience in Python & SQL, improving dashboard efficiency by 40%. Now seeking AI roles in NLP or ML model development."
2. Walls of Text, Zero Structure
If your resume looks like a research paper, it’s game over.
Use bullet points, bold headings, and white space to create a visually digestible format. In the AI job market, clarity is currency.
Pro Tip: Stick to fonts like Helvetica, Arial, or Calibri. Keep it to one page (max two if you're experienced).
3. No Keywords = No Visibility
If your resume doesn’t include the right keywords, ATS (Applicant Tracking Systems) will filter you out before a human even sees it.
SEO Optimised Keywords for AI Roles:
- Machine Learning
- Python
- TensorFlow
- NLP
- Data Analysis
- Prompt Engineering
- Hugging Face
- AI model deployment
Use these organically, don’t keyword stuff, but do mirror the job description.
4. Irrelevant Work Experience
Listing your college internship at a bakery won’t help your case when applying for a Generative AI role.
Instead: Highlight projects or freelance gigs that show real skills. Even Kaggle competitions, GitHub repos, or Rabbit Learning course projects matter.
5. Inconsistent Dates & Gaps with No Explanation
HRs are fine with gaps, as long as they’re explained. What can they not tolerate? Confusion.
Fix It: Add a one liner like:
"Career break to pursue AI certification & freelance data projects (Jan–Jul 2024)"
6. Typos & Grammar Errors
It’s not just about language; it signals a lack of attention to detail. In AI jobs where precision is crucial, this is a deal breaker.
Tip: Use Grammarly. Then ask a friend. Then review again.
7. No Metrics, Just Duties
Listing tasks isn’t enough. HRs want results.
Weak:
"Worked on data cleaning"
Strong:
"Cleaned and pre processed 5M+ records using Python, improving model accuracy by 12%"
8. No Links = No Proof
In tech hiring, you need to back your claims.
Add links to:
- GitHub
- Portfolio
- AI certifications (Udemy, edX, Coursera, Rabbit Learning, etc.)
9. Using Outdated Templates
If you’re still using MS Word templates from 2010, it’s time for a change.
Use:
- Canva
- NovoResume
- Notion
- AI generated layouts (but check formatting!)
10. Copy Paste Syndrome
Applying to 20 roles with the same resume? HRs can tell.
Fix: Tailor each application. Modify the summary, skill highlights, and project relevance.
Bonus Tip: AI Resume Optimisation
Use AI powered resume scanners (like the one on getainaukri.com) to:
- Match your resume to the JD keywords
- Score your resume
- Get actionable insights to improve visibility
Final Thoughts on How Not to Get Ignored
Your resume is your first impression, make it smart, sharp, and strategic.
Avoiding these red flags can increase your chances of interview callbacks, especially in competitive AI job markets.
Looking for resume help tailored to AI jobs?
Try the Resume Builder on getainaukri.com now.