by Erskine Williams, VP of Delivery at Synaptiq
The first step on your journey to a career in computer vision (after obtaining the necessary skills, of course) is to craft a resume which helps you land that first job. In my 16+ years of hiring technical resources, I’ve seen thousands of resumes, not to mention a few dozen iterations of my own resume. There are some easy rules of thumb to follow which will help your resume not only get in front of the hiring manager – but also lead to an interview.
The key point to keep in mind when writing your resume is to consider your target audience. There are typically two steps in the process to landing an interview: you must get past a paid recruiter, and then you must impress the hiring manager enough for them to want to speak with you. Let’s focus on impressing the hiring manager.
The hiring manager will be very busy. They will only be able to dedicate a few fleeting moments at a time to the task of sifting through the resumes screened by the recruiter. Therefore, recognize that your resume will be scanned very quickly, so brevity is of the essence. Your resume should fit on one page, or at most two. Anything longer will frustrate and annoy a busy hiring manager.
In the spirit of keeping things short, avoid laundry lists of tools and technologies. A concise list of the tools you are most proficient in is fine, but listing the kitchen sink on your resume invites skepticism - it’s hard to master all of the tools and techniques in the computer vision/machine learning universe. Be honest about what you’re best at.
When describing your work experience, focus on business outcomes. Hiring managers value candidates who demonstrate a grasp of why the problem is important to solve, and not just how to solve it. Briefly describe the tools or techniques you applied to solve the problem, and focus especially on creative approaches you took that no one else considered.
Unless the hiring manager is simply looking to fill a role with a warm body (and trust me, you don’t want to work for them!), they will be looking for your resume to tell a story - to describe your career trajectory. I typically look for 2 or more years of tenure at each position, as well as some indication of increasing scope and responsibility.
Even if your past experience isn’t in computer vision, it’s important to capture it so the hiring manager can get a feel for your career trajectory and what sort of employee you are likely to be. However, you should insert a section describing whatever computer vision relevant experience you do have (coursework, pet projects, internships, etc.) above your past work experience that may be less relevant to computer vision so that it draws attention first.
Bonus points are awarded to candidates who provide your GitHub handle and/or links to pet projects you may have been working on in your spare time. These are strong indicators of motivation and intellectual curiosity – highly desirable attributes in a job seeker.
For extra-extra credit, consider compiling a portfolio of your academic work, side projects, or professional work (make sure your former employer will allow it). A concise visual overview of your most interesting work with pictures, graphs or figures helps your application rise above the rest.
The last bit of advice is to proofread your resume, and get multiple friends or family members to review it looking for errors. Pay close attention to spelling, grammar, tense and voice of your resume to confirm it sets a professional tone.
The internet is bursting with advice on how to write an effective resume, and I encourage you to do some searching to find other useful nuggets. I hope the above recommendations are useful in your journey to build a rewarding career in computer vision.
About the Author
Erskine Williams began his career as an engineer at Intel, before moving on to write molecular modeling software for Fujitsu BioSciences. Erskine then grew professional services revenue at Jive Software 100% year over year for four years before Jive’s IPO in 2011. Most recently, Erskine held key engineering leadership positions at eBay as Director of Mobile Architecture and Head of Americas Regional Development. Erskine’s 20+ years of engineering and product management experience ensure Synaptiq’s clients achieve their objectives with high impact AI-enabled solutions. Erskine has a B.A. in Cognitive Science and Biochemistry from the University of Virginia. He enjoys fly fishing, mountain biking, and skiing.