As an AI engineering student, I’m sure you’re no stranger to the frustration of applying to internships with no response. I recently found myself in the same shoes, wondering if my resume was the problem. With no industry connections to turn to, I turned to the internet for help. And that’s exactly what I got.
## The Problem with My Resume
I had a hunch that my resume might be the culprit, but I wasn’t sure what was wrong. Was my template not recruiter-friendly? Was it too long or too detailed? Was I not highlighting the right skills and experiences?
## What Recruiters Look for in an AI/ML Candidate’s Resume
To get to the bottom of this, I asked for feedback from people working in AI/ML engineering and recruitment. Here’s what I learned:
* Relevance is key: Make sure your projects and skills are relevant to the internship you’re applying for.
* Impact over details: Instead of listing every detail of your projects, focus on the impact you made. How did your project benefit the company or community?
* Keep it concise: Try to keep your resume to one or two pages at most. Recruiters are busy and don’t have time to read through a novel.
## Tips for Making Your Resume Stand Out
So, how can you make your resume stand out in a sea of applicants? Here are some tips:
* Use keywords: Use keywords related to AI/ML to help your resume pass through applicant tracking systems.
* Highlight transferable skills: Even if you don’t have direct experience in AI/ML, highlight transferable skills like programming languages or data analysis.
* Get feedback: Don’t be afraid to ask for feedback from professors, peers, or even online communities.
## Final Thought
Getting zero responses to your internship applications can be discouraging, but it doesn’t mean you’re not qualified. Take a step back, reassess your resume, and try again. With these tips, you can increase your chances of landing an internship in AI/ML engineering.
Further reading: Resume building tips for AI/ML engineers