In the five days from July 24th to 28th 2017, I interviewed at LinkedIn, Salesforce Einstein, Google, Airbnb, and Facebook, and got all five job offers.
It was a great experience, and I feel fortunate that my efforts paid off, so I decided to write something about it. I will discuss how I prepared, review the interview process, and share my impressions about the five companies.
How it started
I had been at Groupon for almost three years. It’s my first job, and I have been working with an amazing team and on awesome projects. We’ve been building cool stuff, making impact within the company, publishing papers and all that. But I felt my learning rate was being annealed (read: slowing down) yet my mind was craving more. Also as a software engineer in Chicago, there are so many great companies that all attract me in the Bay Area.
Life is short, and professional life shorter still. After talking with my wife and gaining her full support, I decided to take actions and make my first ever career change.
Preparation
Although I’m interested in machine learning positions, the positions at the five companies are slightly different in the title and the interviewing process. Three are machine learning engineer (LinkedIn, Google, Facebook), one is data engineer (Salesforce), and one is software engineer in general (Airbnb). Therefore I needed to prepare for three different areas: coding, machine learning, and system design.
Since I also have a full time job, it took me 2–3 months in total to prepare. Here is how I prepared for the three areas.
Coding
While I agree that coding interviews might not be the best way to assess all your skills as a developer, there is arguably no better way to tell if you are a good engineer in a short period of time. IMO it is the necessary evil to get you that job.
System design
This area is more closely related to the actual working experience. Many questions can be asked during system design interviews, including but not limited to system architecture, object oriented design，database schema design，distributed system design，scalability, etc.
There are many resources online that can help you with the preparation. For the most part I read articles on system design interviews, architectures of large-scale systems, and case studies.
Machine learning
Machine learning interviews can be divided into two aspects, theory and product design.
Unless you are have experience in machine learning research or did really well in your ML course, it helps to read some textbooks. Classical ones such as the Elements of Statistical Learning and Pattern Recognition and Machine Learning are great choices, and if you are interested in specific areas you can read more on those.
The interview process
I started by replying to HR’s messages on LinkedIn, and asking for referrals. After a failed attempt at a rock star startup (which I will touch upon later), I prepared hard for several months, and with help from my recruiters, I scheduled a full week of onsites in the Bay Area. I flew in on Sunday, had five full days of interviews with around 30 interviewers at some best tech companies in the world, and very luckily, got job offers from all five of them.
Phone screening
All phone screenings are standard. The only difference is in the duration: For some companies like LinkedIn it’s one hour, while for Facebook and Airbnb it’s 45 minutes.
Proficiency is the key here, since you are under the time gun and usually you only get one chance. You would have to very quickly recognize the type of problem and give a high-level solution. Be sure to talk to the interviewer about your thinking and intentions. It might slow you down a little at the beginning, but communication is more important than anything and it only helps with the interview. Do not recite the solution as the interviewer would almost certainly see through it.
One good thing about interviewing with multiple companies at the same time is that it gives you certain advantages. I was able to skip the second round phone screening with Airbnb and Salesforce because I got the onsite at LinkedIn and Facebook after only one phone screening.
More surprisingly, Google even let me skip their phone screening entirely and schedule my onsite to fill the vacancy after learning I had four onsites coming in the next week. I knew it was going to make it extremely tiring, but hey, nobody can refuse a Google onsite invitation!
Onsite
This is my first onsite and I interviewed at the Sunnyvale location. The office is very neat and people look very professional, as always.
The sessions are one hour each. Coding questions are standard, but the ML questions can get a bit tough. That said, I got an email from my HR containing the preparation material which was very helpful, and in the end I did not see anything that was too surprising. I heard the rumor that LinkedIn has the best meals in the Silicon Valley, and from what I saw if it’s not true, it’s not too far from the truth.
Acquisition by Microsoft seems to have lifted the financial burden from LinkedIn, and freed them up to do really cool things. New features such as videos and professional advertisements are exciting. As a company focusing on professional development, LinkedIn prioritizes the growth of its own employees. A lot of teams such as ads relevance and feed ranking are expanding, so act quickly if you want to join.
Salesforce Einstein
Rock star project by rock star team. The team is pretty new and feels very much like a startup. The product is built on the Scala stack, so type safety is a real thing there! Great talks on the Optimus Prime library by Matthew Tovbin at Scala Days Chicago 2017 and Leah McGuire at Spark Summit West 2017.
I interviewed at their Palo Alto office. The team has a cohesive culture and work life balance is great there. Everybody is passionate about what they are doing and really enjoys it. With four sessions it is shorter compared to the other onsite interviews, but I wish I could have stayed longer. After the interview Matthew even took me for a walk to the HP garage :)
Absolutely the industry leader, and nothing to say about it that people don’t already know. But it’s huge. Like, really, really HUGE. It took me 20 minutes to ride a bicycle to meet my friends there. Also lines for food can be too long. Forever a great place for developers.
I interviewed at one of the many buildings on the Mountain View campus, and I don’t know which one it is because it’s HUGE.
My interviewers all look very smart, and once they start talking they are even smarter. It would be very enjoyable to work with these people.
One thing that I felt special about Google’s interviews is that the analysis of algorithm complexity is really important. Make sure you really understand what Big O notation means!
Airbnb
Fast expanding unicorn with a unique culture and arguably the most beautiful office in the Silicon Valley. New products such as Experiences and restaurant reservation, high end niche market, and expansion into China all contribute to a positive prospect. Perfect choice if you are risk tolerant and want a fast growing, pre-IPO experience.
Airbnb’s coding interview is a bit unique because you’ll be coding in an IDE instead of whiteboarding, so your code needs to compile and give the right answer. Some problems can get really hard.
And they’ve got the one-of-a-kind cross functional interviews. This is how Airbnb takes culture seriously, and being technically excellent doesn’t guarantee a job offer. For me the two cross functionals were really enjoyable. I had casual conversations with the interviewers and we all felt happy at the end of the session.
Overall I think Airbnb’s onsite is the hardest due to the difficulty of the problems, longer duration, and unique cross-functional interviews. If you are interested, be sure to understand their culture and core values.
Another giant that is still growing fast, and smaller and faster-paced compared to Google. With its product lines dominating the social network market and big investments in AI and VR, I can only see more growth potential for Facebook in the future. With stars like Yann LeCun and Yangqing Jia, it’s the perfect place if you are interested in machine learning.
I interviewed at Building 20, the one with the rooftop garden and ocean view and also where Zuckerberg’s office is located.
I’m not sure if the interviewers got instructions, but I didn’t get clear signs whether my solutions were correct, although I believed they were.
By noon the prior four days started to take its toll, and I was having a headache. I persisted through the afternoon sessions but felt I didn’t do well at all. I was a bit surprised to learn that I was getting an offer from them as well.
Generally I felt people there believe the company’s vision and are proud of what they are building. Being a company with half a trillion market cap and growing, Facebook is a perfect place to grow your career at.
Negotiation
This is a big topic that I won’t cover in this post, but I found this article to be very helpful.
Some things that I do think are important:
1.Be professional.
2.Know your leverages.
3.Be genuinely interested in the teams and projects.
4.Keep your patience and confidence.
5.Be determined but polite.
6.Never lie.
Afterthoughts
1.Life is short. Professional life is shorter. Make the right move at the right time.
2.Interviews are not just interviews. They are a perfect time to network and make friends.
3.Always be curious and learn.
4.Negotiation is important for job satisfaction.
5.Getting the job offer only means you meet the minimum requirements. There are no maximum requirements. Keep getting better.
Thanks for reading through this long post. (But for read compelete article you can click link, End of the page)