Getting a job as an NLP engineer: Resume, Resume, Resume

Your resume from the perspective of the hiring manager

Gm all,

This is the fourth post in the series on Getting a job as an NLP engineer. Check out the previous three posts here [1, 2, 3].

Getting job as an NLP engineer: Prerequisites

While there are many guides and templates on how to make a great resume with fantastic templates to follow (check BowTied_Raptor and BowTied Cyber guides), in this post, I would like to offer a different perspective on making the resume. In particular, I would like to start from the perspective of the hiring manager who is looking for great natural language processing (NLP) engineer candidates and help you build your resume backward from his/her requirements. At the end of the day, the hiring manager makes the final call on whether he/she wants you (a prospective candidate) on the team, and making the resume that fits their interest is crucial.

Note, this is different from the recruiter resume filtering stage where recruiters quickly skim your resume making sure that you satisfy the minimum qualifications for this role. Many recruiters for Natural Language Processing engineer jobs know little technical details and can’t fully assess your resume. They quickly scan through your educational background, relevant experience, and skills to make sure you have a bare minimum to let you go through the interviews.

I have seen many different resumes, been through many screenings filtering for the right candidates for the role, and seen many different decisions play out by the hiring managers. This post comes from my experience.

Let’s dive in 👇

What hiring managers look for

Experience

Your experience comes first. No matter whether you have the best credentials in the world working on the biggest tech companies like Google/FB; or graduating from the best universities like MIT; what matters at the end of the day is what you did, how impressive it is, and how is it relevant to the position you are applying.

Ideally, the hiring manager is looking for candidates who are very familiar with the type of work that needs to be done in their desired NLP engineer opening position. However, each job comes with its own unique requirements that are almost impossible to replicate unless you are at that job.

So in reality, the hiring manager is looking first and foremost for a candidate who has the most relevant experience to their NLP job opening. There are always exceptions as in the case of the junior candidates where experience has less emphasis. But even in the case of the junior candidate having relevant personal projects will make you stand out. Similarly, if you are finishing college or a Ph.D., you are expected to have more academic experience rather than work experience in the industry.

Many people likely don’t have much experience in the natural language processing space (in fact NLP boom after deep learning success started merely 10 years ago). Having 1-2 strong projects will make you stand out from the rest of the applicants. I have written a blog post on how to build a strong portfolio, so check it out:

Getting a job as an NLP engineer: Building kick-ass portfolio of projects for your resume

How to present your experience in the resume

When listing your projects and relevant experience in the resume I suggest you follow the following template:

Name of the project; Place where you worked on it. Dates

Short description of the project describing what the project does, what kind of natural language processing technology it uses (on high level); other libraries and frameworks you used to build it.

Summarize the highlights of this work. Could be in the form of number of daily users, tweets featuring your work, and acknowledgments or praises from others.

For example:

Lexica.art; Personal project Summer 2022 - Ongoing

A search engine for generated images by text-to-image AI stable diffusion. Crawled a large corpus of text prompts from Discord, generated these images using server-less GPUs, and indexed them using very efficient FAISS nearest-neighbor library. Applied custom NSFW filter to remove unsafe images from search.

Users have viewed 290 million images per week using this platform. Raised 5 million USD.

Credentials

Despite tech being quite ahead of many other industries and primarily evaluating candidates based on their merit rather than their credentials; credentials still do matter.

Assuming that you have two candidates with similar experience and quality of the projects in the portfolio; the hiring manager will likely hire a candidate from a more famous school or more reputable employer.

So if you are studying or graduated from a good school; put it on the top of your resume. This will likely improve the first impression of the hiring manager as he/she is looking over your resume. Including relevant coursework and a high GPA is a nice bonus.

References

Pretty much every time the offer is made, the recruiters ask you to give the contact of 2/3 people that can provide short references for you. While this is somewhat expected and treated as an afterthought many times, I suggest taking the opposite action and providing references in your resume.

Having a reputable name listed as a reference in your resume will give a big boost to your credibility when the hiring manager is looking at your resume.

Put the reference contacts at the end of the resume. Don’t list more than three people. Prioritize more reputable people and people with more years of experience first. Here is a short template for you to list your references.

Name of the person; Current Position

Short description on how you know them and how you interacted with them

For example

Person ABC; Senior ML engineer at company XYZ

Current mentor. Worked together on building text classifiers for company XYZ that reached 1M+ customers.

General tips for building your resume

If I could only write a single sentence in this section, I would simply suggest striving towards summarizing all your accomplishments in one 2-3 short paragraphs. That means keeping the most impressive accomplishments in your resume and removing everything else.

But here is the longer version of it:

1. Keep it short.

   1. The shorter it is the better. 1 page is great, and 2-3 pages are good as well (unless you are super senior with tons of experience and accomplishments).

   2. The hiring managers and interviewers would all appreciate spending less time looking over your resume to understand whether you fit into the advertised role.

2. Put your most impressive accomplishments first.

3. Cut out old accomplishments from the resume.

   1. Especially if those don’t fit in your resume narrative.

4. Don’t reinvent the wheel.

   1. The less friction there is to read your resume the better it is.

      1. Don’t change small things like fonts that don’t really matter when making hiring decisions.

   2. Re-use the resume templates of people that landed the desired NLP engineer job.

      1. Feel free to email and ask them to send a LaTeX or Word file with their resume. I did it once by asking a more senior and successful colleague to send his resume. Still using the same template.

Conclusions

I realize that this blog doesn’t only apply to the field of Machine Learning and Natural Language Processing, and can be generally applied to many other positions in tech.

If you liked this post and you know someone who would benefit from it, please send it to them. I would greatly appreciate you spreading the good word about my newsletter.

If you have questions feel free to message me on Twitter.

See you soon!