How to stand out when applying for ML engineering positions at high-profile companies?

Question

Hey everyone,

I'm a senior ML engineer (~4.5 years exp) working at a medium-sized company. My educational background is a BSc and MSc in computer engineering from a not super fancy university in Europe. I wrote a few papers during my university years and as a result of hobby projects, but these were published in mediocre conferences (so not Neurips/ACL-level).

I tried applying to a few ML engineering jobs in the past couple of months (Spotify, Apple and Amazon) but did not hear back. I searched through Linkedin to see the backgrounds of ML engineers working at these companies in my area just to get an idea of the situation. My impression was that a vast majority of these people went to top-tier universities (significant number of people have a Phd), interned at FAANG during their university years, wrote (or contributed to) papers in top ML conferences etc.

I know that ML engineering positions are very competitive at these companies & also the market is very tough now in general, but it got me wondering:

What should someone like me work on to increase my chances of joining one of these companies as a ML engineer? The patterns I see from people working there is hard to achieve at this stage in my life as:

I already have a MSc degree and doing another one at a better university does not really make sense
Since I'm working as a senior engineer, I don't know if applying for internships positions (even if it's FAANG) is a sensible choice
Writing top-tier papers is incredibly time consuming and hardly possible with maintaining a full time job. To be honest, I tried to do this in the past (since I know publications at top-tier conferences matter a lot in these situations), but it really affected my personal life. This is almost like trying to do two full-time jobs, which messed up my WLB.

Some things I was thinking about focusing on that could help me stand out:

Writing technical blogposts to our company's engineering blog.
Apply to meetups or conferences as a speaker.
Certifications (I was thinking of something like CKAD or AWS Certified Machine Learning - Specialty)
Focus on promotion to staff/principal MLE. It may be easier to step into a higher tier company by down-leveling.
Keep trying to do research/writing papers as a side project, but need to figure out how to do this without burning out.

I honestly don't know if the above sound sensible, so I'd love to hear your opinion on this or if you have any additional ideas.

Casey Dai · Accepted Answer

Don't overthink it.  Ask yourself what the top 3-5 problems that MLE managers deal with on a regular basis.*  Based on your answer to that (it doesn't have to be 100% accurate), build your profile around being a solution provider for those problems. You'll soon realize that to have a very well-thought out solution takes a lot of work, which is a great forcing function to narrow things down.  As a former hiring manager, a track record and verifiable expertise in problem solving is by far my #1 criteria.*  After getting clarity on that you'll realize what the best medium is to communicate that message. Your intuition is correct that publishing papers and getting advanced degrees are very expensive and time consuming options to achieve what you want.  Start with easier options* such as writing up a blog post vs. publishing a paper. Getting a cert is generally not needed IMO since it's a proxy for you having certain knowledge. A better way is to showcase you have that expertise by building a body of work (ideally discoverable online).  Blogging and posting on socials are good accessible options. Getting speaking gigs is great, but it doesn't have to be at a major conference at the beginning. It can be as simple as picking a topic and putting together a 30-minute presentation with a 30-minute Q&A on Taro. For example, I did one earlier this year to get some of my ideas out there.

How to stand out when applying for ML engineering positions at high-profile companies?

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