During the five days from July 24th to 28th, 2017, a Chinese-born technical engineer, Zeng Xiaohan, interviewed five Silicon Valley technology giants, including LinkedIn, Salesforce, Google, Airbnb and Facebook, and eventually all received Offer.
Prior to this, authors who were not professional in computer science, short in working hours, and limited in knowledge and experience, did not lose confidence after a failed interview, but came from the beginning. As a full-time author, it is indeed very fortunate to have an interview at the leisure time and get the offer of five technology giants at the same time, but the efforts behind it cannot be ignored. In this article, I will share with you the preparations, interview techniques and some practical experiences of the authors in the face of five different technology companies and different positions. I hope that I can help some engineers who are preparing to change jobs.
The following is the translation:
Initial cause
The reason is 2017, this year, as an ordinary software development engineer, I have been working at the Groupon Chicago headquarters for nearly three years. This is my first job, my team and projects are very good, we build cool things together, play their own influence within the company, publish papers and so on. However, work is easy and life is at ease. Over time, I found that my learning speed is gradually slowing down, and my heart is beginning to hope for new challenges. At the same time, as a code worker who has lived in Chicago for eight years, he is also very interested in the excellent companies in the Bay Area.
Life is short and your career is shorter. After communicating with my wife and getting her full support, I decided to take action to make the first career change.
ready
First of all, I am very interested in the position of machine learning, but in fact, the job title and interview process of my application for these five companies are slightly different. LinkedIn, Google, and Facebook are machine learning engineers, Salesforce is a data engineer, and Airbnb is a software engineer. So I need to prepare three different areas: algorithms and programming, machine learning, and system design.
Since there is still a full-time job during the day, I can only take some time to prepare for the interview at night. In general, it took a total of 2-3 months. Here's how I prepare for these three aspects.
Algorithm and programming
Indeed, algorithms and programming interviews are not the best way to assess all of the developer's skills, but there is no better way to judge whether it is a good engineer in a short time.
This piece is actually the best and the hardest to prepare. On the one hand, there are a lot of websites that offer a lot of questions to practice, and on the other hand, they need to invest a lot of time and energy. I mainly use Leetcode and Geeksforgeeks to practice, and also recommend Hackerrank and Lintcode. I spent a few weeks going through the common data structures and algorithms, then focused on areas that I was not familiar with, and finally solved some common problems. Since I have limited time, I usually do two questions every day.
My opinion is:
More practice, no shortcuts.
Instead of completing all 600 questions on Leetcode, it's better to cover all types and thoroughly understand each question. I have done about 70 questions in total, which I think is enough. My idea is that if the 70 questions haven't helped, then you may have a problem with the method. It doesn't help to do 700.
Doing the hardest questions will make the rest easier.
If you can't finish a question for more than two hours, you can see the answer. It is not worthwhile to spend time thinking.
Be sure to read the answer after completing a question. I admire those who have a line of Python code to solve the problem, although sometimes rely on a certain feature of the language, but it is very subtle.
Use the most common language you are familiar with and use it during an interview.
system design
The field of system design is more closely related to actual work experience. If you have a lot of experience in system design, you can spend less time. Although it is very experienced, it can still be prepared. There are also many experience stickers and exercises on the Internet. I mainly read articles about system design interviews, large system architectures, and case studies.
Personally feel that there are many problems involved in this field interview, including but not limited to system architecture, object-oriented design, database schema design, distributed system design, scalability and so on. Because my main interview position is machine learning related, this interview encountered fewer sessions (mainly Airbnb).
Although the system design interview will cover many topics, there are some general ideas on how to answer these questions:
First understand the requirements, then consider the big framework, and finally the specific design. Don't jump to the details right away without figuring out what the requirements are.
There is no perfect system design. Make trade-offs as needed.
Still, the best way to prepare for a system design interview is to sit down and design a system that explores the tools, frameworks, and libraries you normally use. For example, if HBase is used in the work, some people may simply use the Client to run some DDL and do some Get, but some people may ingest some designs that understand the whole system, including the entire read/ Write processes, how to ensure strong consistency, secondary/primary compression, LRU cache, and the role of Bloom Filter. You can even compare HBase and Cassandra to see similarities and differences in their design. If you are asked to design a distributed key-value store during an interview, you won't feel too suddenly.
Many blogs also provide a lot of knowledge, such as Hacker Noon, some companies' engineering blogs, and official documentation for open source projects.
The most important thing is to be curious and modest. Absorb the nutrients of knowledge like a sponge.
Machine learning
Machine learning interviews can be divided into two aspects: theory and product design.
Unless you have a lot of experience in machine learning or machine learning, it is helpful to read some textbooks. Classic textbooks such as The Elements of Statistical Learning and Pattern Recognition and Machine Learning are very helpful. If you are interested in a particular field, you can read more.
Make sure you understand basic concepts such as bias/variance tradeoffs, overfitting, gradient descent, L1/L2 regularization, Bayes' theorem, collaborative filtering, and dimensionality reduction. Familiar with common formulas and model derivations, such as Bayes' theorem, such as logistic regression and support vector machines. Try to implement simple models such as decision trees and K-means clustering. If you mention some models on your resume, make sure you fully understand them and evaluate their strengths and weaknesses.
For machine learning product design, learn about the general process of building machine learning products. I did this:
Find out what the goal is: forecasting, recommending, clustering, searching, and more.
Choose the right algorithm: supervised and unsupervised, classified and regressed, generalized linear model/decision tree/neural network. Give reasons for the choices made.
Select/design related functions based on available data.
Select model performance metrics.
Consider how to optimize the model for production.
I want to emphasize the importance of maintaining curiosity and continuous learning. Don't just use Spark MLlib or XGBoost to simply call the API to train a model. I'd recommend studying why Stochastic gradient descent is suitable for distributed training, or what is the difference between XGBoost and the usual GBDT, including what is the definition of Loss Function? In particular, why use second-order guides and so on.
Interview process
At the beginning, I replied to HR's message on LinkedIn and asked him to recommend a position for me. After a star startup failed to find a job (I talked later), I worked hard for several months, and with the help of HR, I arranged a full week of on-site interviews in the Bay Area. I arrived in the Bay Area on Sunday and interviewed about 30 interviewers in five days in the world's best technology companies. Fortunately, I got the job opportunities of these five companies.
Phone interview
All phone interviews are standard. The only difference is the interview time: LinkedIn for 1 hour, while Facebook and Airbnb are 45 minutes.
Proficiency is the key to a telephone interview, because time is limited and usually you only have one chance. You must quickly determine the type of problem and give a macro solution. Be sure to communicate your thoughts with the interviewer and explain your intentions. This may make you slower at first, but communication is more important than anything and will be very helpful for the interview. Don't give up the answer, because the interviewer will definitely see it at a glance.
For machine learning positions, some companies ask questions about machine learning, so review the knowledge and skills in machine learning before the interview.
In order to make better use of my time, I had three phone interviews in the same afternoon, with one hour break between each. This kind of approach may not be suitable for everyone. The advantage is that you can get hot and iron. The downside is that if you don't have a good face, the interview later may be affected.
One of the benefits of multiple companies at the same time is that sometimes it is possible to save some links. Some Silicon Valley companies require two rounds of telephone interviews for interviewers outside the Bay Area. I was able to save Airbnb and Salesforce's second round of phone interviews because the other party got a chance to get a live interview with LinkedIn and Facebook during a round of phone interviews.
What is even more surprising is that Google didn't even have a phone interview and asked me to participate in the on-site interview. This is because the other party learned that I am going to the Bay Area to participate in four on-site interviews next week. I know this will make me very tired, but no one will reject Google's live interview invitation!
On-site interview
Although the five companies are all IT companies, they are in different fields and have different cultures. I will simply talk about how I feel about them. In addition, although it is not considered to be food, but as a Chinese food for the people, it is natural to have a comment on lunch.
This is my first live interview, I am at the Sunnyvale office at LinkedIn. As a company focused on socializing in the workplace, LinkedIn is characterized by dignity, atmosphere, professionalism, and internal culture is also very professional. The employees are dressed in business casual wear, giving the overall feeling of a career elite, which fits well with their purpose.
For interviews, programming and machine learning are 1 hour each. Programming interviews are standard questions, but machine learning interviews can be difficult. Despite this, I received an email from HR that contained very useful preparation materials, so there was nothing too unexpected in the interview. I heard that LinkedIn has the best canteen in Silicon Valley. From my actual experience, this is almost true.
After LinkedIn's acquisition by Microsoft, there was less economic pressure, so that it could let go of the very cool things. The new additions to LinkedIn and professional advertising are exciting. As a company focused on career development, LinkedIn prioritizes the career growth of its employees. At present, many groups including ads relevance and feed ranking are recruiting, so if you want to join, then act quickly.
Salesforce Einstein
Einstein is the star product of Salesforce in recent years, with a star team. This team is very new and feels very much like a startup. The team mainly uses Scala, and the Tech stack is Akka/Play/Spark, which is the most attractive point for me. I first came into contact with Einstein, who listened to Matthew's "Type safety in machine learning" speech at ScalaDays in April 2017, and then listened to Leah's speech at Spark Summit West. People who like Scala must not miss it.
The interview location is Salesforce's office in Palo Alto. This team is very cohesive and can balance work and life. Everyone loves and truly enjoys what they do. Compared to other on-site interviews, the four sessions have a slightly shorter total time, with a general focus on Data engineering and System design. Another thing to note is that coding is also going to run on the machine. After the interview, Matthew even took me to visit the HP garage.
There is nothing to say about the leaders in the industry today. The most important impression is big, very, very big. I went on a bike ride for 20 minutes while I met my Google friend. There are a lot of people waiting for dinner at noon.
I was interviewing in a building in many of Mountain View's buildings. I don't know which one is specific, because Google is really big.
The interviewers look very young and they look smart when they speak. Working with them must be very enjoyable.
It's worth noting that Google places special emphasis on the complexity of the algorithm, ensuring that you really understand the complexity of time and space and can optimize for bottlenecks! This is different from other companies.
Airbnb
The fast-expanding Unicorn company has a very unique corporate culture and may be the most beautiful office in Silicon Valley. The introduction of new products including “experience†and restaurant reservation services, trials in high-end niche markets, and access to the Chinese market have all added positive factors to Airbnb's prospects. If you can afford high risk and want a fast-growing pre-IPO experience, then Airbnb is the perfect choice.
Airbnb's coding interview is a bit unique, requires a computer, and each session is only 45 minutes, and some topics are quite difficult, so the pressure is not small.
Airbnb's unique cross-functional interview is also my favorite, and I can easily communicate with the interviewer. Airbnb takes the company culture seriously, and technical excellence does not guarantee the offer.
In general, I think Airbnb's on-site interview process is the longest, the most links, the problems are difficult, and the overall feeling is the most tired. If you are interested, be sure to understand their culture and core values.
Another giant that is still growing at a high speed is smaller and faster than Google. In the social networking market, a comprehensive product line, a monopoly position, and a large investment in AI and VR have been launched, and Facebook has only more growth potential in the future. There are stars like Yann LeCun and Yangqing Jia, which is a perfect place if you are interested in machine learning.
My interview was on the roof of the building with a garden sea view room Building 20, which is also the place where Zuckerberg works.
I feel the worst of Facebook's entire interview process. On the one hand, because it is already the fifth interview, the whole person is already very tired. In addition, it may be Facebook's regulations. The interviewer did not give me a special answer. Obviously good and bad signals, although I feel that my answer is not wrong, but I am slightly uncertain about my performance.
The two Codings are still normal. The two questions are given a total of two solutions under the reminder of the interviewer. One question was asked twice. In the afternoon, I already felt that I was ill, and my headache was very bad. In the end, I finished the interview with hard support. After I came out, I didn’t feel very good. I didn’t expect to get the Offer.
Overall, I feel that Facebook staff are convinced of their company vision and are proud of what they are building. As a company with a market capitalization of 5 trillion, Facebook is a great place for your career.
Wage negotiation
Many people feel that they are not good at negotiation, or often embarrassed to speak. I personally feel that job hunting is actually selling my time, and time is the only non-renewable resource for a person. If you feel that your time is not worthwhile, then others will not think it is worth it.
This is a big topic, I am not going to discuss it in depth here, but I found this article very helpful.
There are a few points I think are worth noting:
Maintain professionalism.
Know your chips.
Show your interest in the team and the project.
Be patient and confident.
A firm attitude, but be polite.
Never lie.
My failed interview at Databricks
All success begins with failure, including interviews. Before I started interviewing these five companies, my interview at Databricks failed in May.
As early as April, Xiangrui, the manager of the Spark MLlib group, contacted me on LinkedIn and asked if I was interested in a position in the Spark MLlib team. I was flattered and thought it was a great opportunity.
I work with Spark and I really like Scala;
The strength of Databricks engineers is first class;
Spark is revolutionizing the entire world of big data.
This is an opportunity that I can't miss, so I simply started the interview process in two days.
Databricks' level requirements are very high and the process is quite lengthy, including a preliminary screening questionnaire, a telephone interview, a coding assignment, and a final on-site interview.
I got an on-site interview invitation and visited the office in downtown San Francisco to see the bay.
My interviewer is very smart but equally humble. During the interview, I often feel that I have been pushed to the limit. In the afternoon, there was a round of machine learning algorithm theory. On the one hand, the strength of the machine was insufficient, on the other hand, the preparation was insufficient, and the whole link was a disaster. Finally, I chatted briefly with Xiangrui.
I received a rejection letter a few days later, which was expected, but I was depressed for several days. Although there is no opportunity to work at Databricks, I believe they can continue to create greater impact and achievements.
postscript
Life is short and his career is shorter. Make the right move at the right time.
Concentrated interviews are very tiring, but they will also give you a big advantage.
Interview is not only a process of finding a job, but also an opportunity to make friends. The Silicon Valley circle is just that big.
Usually have the opportunity to make more friends, such as a meeting is a great opportunity. The interview opportunities for Databricks, Salesforce, and Airbnb are all based on the Spark Summit and Scala Days I've been to.
Getting the Offer only means that you have met the company's minimum standards. The highest standards are not on the line, so keep improving.
From the first interview in May to the last interview at the end of September, I completed my first career quit, and the process was long and difficult.
The preparation process is still very hard, because I have to continue my job. There was a time when I was going to sleep until one o'clock in the morning every night. I got up at 8:30 in the morning and went to work.
Interviewing five companies in five days is also highly stressful and highly risky. I don't recommend doing this unless you have a tight time. But if you get a few Offer, you will have a big advantage when it comes to paying.
Finally, thanks to all the friends who helped me to give me advice in the process. Thanks to all the companies that gave me the interview opportunity and offer, the HR that I have been in contact with, and everyone who took the time to chat with me. I am also grateful to my family who have been silently supporting me – my dear wife who is looking at my growing parents, everything I have done for me, and my daughter who smiles warmly every day.
2.54mm (0.1") Pitch Female Headers
Overview
The most commonly seen female headers are 2.54mm (0.1") single or double row female/socket headers. These female headers together with its male counterpart are used in connecting Arduino boards and shields together. 2.54mm pitch female sockets/headers are low-profile connectors designed for signal and low power PC board connections when space is at a premium. They have the perfect height for clearing the USB-B connector and great for stacking multiple shields.
Since 2.54mm pitch female header is commonly used in a lot of applications, Scondar offers numerous options for this type of female header. Orientation can either be SMT or THM, single, dual or triple row. Antenk offers 2.54mm pitch female headers in either vertical or right-angle orientation. The pins and blades are also available in various sizes, counts, amperages, and plating.
The 2.54mm can accommodate a maximum current of 3A, with a 30 to 22 AWG wire size, and up to 40-positions. Antenk offers these female headers in high quality and affordable China-quoted price that snuggly fits with the pins of a male header and acts as a receptacle.
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Applications of 2.54mm Pitch Female Headers
Electronics:
LED applications
Arduino boards
Arduino Pro
Arduino Mega
Solar applications
Weighing systems
Appliances:
Air conditioner
Refrigerator
Microwave oven
Washing machine
Water heater
Shower toilet
Washer/Dryer
Stove
Automotive, Heavy Duty Military and Marine
For densely packed equipment requiring weight reduction and downsizing and for tough and harsh conditions.
Vehicle infotainment
Computer peripherals
Battery Connections
Battery connections rely on the ability of the current to pass reliable and solid current. This prevents overheating in the circuit and voltage drop.
Rechargeable battery packs
Battery balancers
Battery eliminator circuits
Medical Diagnostic and Monitoring equipment
Heart monitors
Telecoms
Datacoms
Mount Type: Through-hole vs Surface Mount
At one side of this female header is a series of pins which can either be mounted and soldered directly onto the surface of the PCB (SMT) or placed into drilled holes on the PCB (THM).
Through-Hole (Poke-In)
Best used for high-reliability products that require stronger connections between layers.Aerospace and military products are most likely to require this type of mounting as these products experience extreme accelerations, collisions, or high temperatures.
Useful in test and prototyping applications that sometimes require manual adjustments and replacements.
2.54mm, 1-row vertical female header, 2.54mm, 2-row vertical female header, 2.54mm, 3-row vertical female header, 2.54mm, 1-row right-angle female header and 2.54mm, 2-row right-angle female header, 2.54mm U-
Shaped Female header, 2.54mm U-Shaped Dual Row Female header are examples of Antenk products with through-hole mount type.
Surface-Mount
The most common electronic hardware requirements are SMT.
Essential in PCB design and manufacturing, having improved the quality and performance of PCBs overall.
Cost of processing and handling is reduced.
SMT components can be mounted on both side of the board.
Ability to fit a high number of small components on a PCB has allowed for much denser, higher performing, and smaller PCBs.
2.54mm, 2-row right-angle female header and 2.54mm, 1-row right-angle female header are Antenk`s featured SMT female headers.
Orientation/Pin-Type: Vertical (Straight), Right-Angle and U-Shaped
2.54mm pitch female headers may be further classified into pin orientation as well, such as vertical or straight female header, right-angle female header or U-shaped female header.
Vertical or Straight Female Header Orientation
One side of the series of pins is connected to PCB board in which the pins can be at a right-angle to the PCB surface (usually called "straight" or [vertical") or..
Right-Angle Female Header Orientation
Parallel to the board's surface (referred to as "right-angle" pins).
U-Shaped Female Header Orientation
U-shaped orientation is characterized by the shape of the pins at one side of the header, forming a letter [U". It is often chosen for applications where repeat mating cycles are not required as it can also be used and soldered directly to both PCB's.
Each of these pin-types have different applications that fit with their specific configuration.
Single, Dual or Multiple Number of Rows
For a 2.54mm straight or vertical female header, the standard number of rows that Antenk offers ranges from 1 to 2 rows. However, customization can be available if 3, 4 or n number of rows is needed by the customer. Also, the number of contacts for the single row is about 2-40 pins while for dual row, the number contacts may vary from 2-80 pins.
Pin Material
The pins of the connector attached to the board have been designed with copper alloy. With customer`s demand the pins can be made gold plated.
Custom 2.54mm Pitch Female Headers
Customizable 2.54 mm pitch female headers are also available, making your manufacturing process way faster as the pins are already inserted in the headers, insulator height is made at the right size and the accurate pin length you require is followed.
Parts are made using semi-automated manufacturing processes that ensure both precision and delicacy in handling the headers before packaging on tape and reel.
Tape and Reel Packaging for SMT Components
Antenk's SMT headers are offered with customizable mating pin lengths, in which each series has multiple number of of circuits, summing up to a thousand individual part number combinations per connector series.
The tape and reel carrier strip ensures that the headers are packaged within accurately sized cavities for its height, width and depth, securing the headers from the environment and maintaining consistent position during transportation.
Antenk also offer a range of custom Tape and reel carrier strip packaging cavities.
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