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Breaking into Artificial Intelligence

The story of an international student who was lost and needed guidance getting started with AI.

Email he sent me.

Meet Hyun

Hyun is an international student who was looking for guidance on how to break into Artificial Intelligence. He was unsure about his career path and whether he should pursue a Master’s or PHD, and what he should do to reach his goals. He also felt inadequate about his skills and the requirements for jobs and internships and feeling like he didn’t meet the standards.

His questions:

The biggest challenge he wanted to address was the application process for internships.

  1. How can I make my resume more attractive towards people of industry? (I feel very invisible when applying for internships)
  2. Could you explain what your first technical interview experience was like?
  3. As an international student, how should I approach companies regarding sponsorship? (Should I ask them during the interview process? Or should I wait?)
  4. What type of skills should I focus on honing to become a stronger candidate for AI related fields? (Are there specific types of internships I should focus more on, research internships vs software engineering internships, etc)

Here’s how Vibhav Altekar— the mentor I matched him with — answered the questions. Vibhav finished engineering at UC Davis this year and has worked at Twitter, researched Deep Learning at UCD and been a KPCB fellow.

Picture of Vibhav in San Francisco.

Vibhav’s Answers

Just want to start off by saying that I felt the same way throughout my college experience in terms of the pain and lack of information about finding internships. I was never able to get an interview at a career fair at UC Davis, and I had no idea what they were looking for. The best thing that I did was put myself in the shoes of the recruiters and tried to understand what they wanted.

Question 1: How can I make my resume more attractive towards people of industry? (I feel very invisible when applying for internships)

In any situation, you want to position yourself to be the best fit for the job role that the recruiter is trying to fill. If its an embedded role, highlight any experience with Arduino/raspberry pi. If it’s a data science role, highlight statistics classes and kaggle competitions etc. You basically want to be the ideal person to go to the job, and know enough to hit the ground running.

I totally understand what you mean when you say you feel invisible. The issue there is that many students when applying to internships, have almost identical resumes. Everyone who takes ECS 40 & 60, highlights the same projects, so all students effectively seem the same. You want to do something that makes you stand out from the crowd, so I highly encourage you to go to as many hackathons as possible, and build cool things, that interest you! Start small and work your way to more complex projects that you can show off on your github or resume.

Also, network really hard. Meet new people, and use the connections you already have to find inroads to companies. Referrals can make a big difference.

Questions 2: Could you explain what your first technical interview experience was like?

I got absolutely destroyed by my first technical interview. If it was an exam, I would have gotten an F.

Story

I had just switched from Chemical Engineering to Electrical Engineering, and my dad’s friend referred me to Apple. When I got an interview for a hardware test team, I was elated. I studied Python scripting, because that is what was mentioned in the job requirements. The initial phone call with the recruiter was underwhelming as all she did was ask questions about what location I preferred and what days I wanted to start on, if I got the job. The technical interview happened next, and the interviewer asked me questions on linked lists and hash tables, which at the time, I had no idea about. I miserably failed the interview and was dejected for 2 weeks. Afterwords, I learned the material, and realized the questions were actually fairly easy if I had studied, so I study a TON of problems on leetcode.com and interviewcake.com. I still failed interviews after that, but I also passed some, and I realized that interviews are just a numbers game. The more experience you have, the easier they become.

Question 3: As an international student, how should I approach companies regarding sponsorship? (Should I ask them during the interview process? Or should I wait?)

I am not an international student so I am not super sure about all the legal details, but I have some friends who have gone through this process.

First, the big companies are much more lenient towards sponsoring work visas, so look for the Amazon, Workday, and Intel type companies. Startups usually do not have the money to sponsor those. Typically, the recruiter will ask you if you need a visa if they are interested in your resume, so there is no real need to bring it up on your own. If the company needs to know, they will always ask.

Questions 4: What type of skills should I focus on honing to become a stronger candidate for AI related fields? (Are there specific types of internships I should focus more on, research internships vs software engineering internships, etc)

Getting an AI job is very different to software engineering, since AI is growing so quickly and rapidly right now. Most AI positions require at least a master’s degree if not a PhD, but there are ways around this, but it is a lot of work. The best thing to do is to study AI in depth. The great thing about learning AI now is that a lot of information is available online for free!

I know you were wondering if it is enough to have a BS degree and work in AI, and the answer is yes, but your work might differ from a person with a PhD. In AI there are many kinds of roles including, research scientist, research engineer, machine learning engineer, machine learning infrastructure etc. There are numerous titles pointing to roughly very similar roles. Most likely, with just a bachelor’s degree, the easiest place to get a job is as a data engineer or machine learning infrastructure engineer. These are the folks who build out things like tensorflow (Google) or AWS Deep learning pipelines (Amazon) or CudNN (Nvidia) libraries. They make build systems and tools so that deep learning models can be easily trained, tested, and deployed. Data engineers also make sure that data pipelines from users/databases are efficiently stored in a way that the ML models can train on them easily.

The research scientists or machine learning engineers, are the people that write the model architectures and test and see if they work with the data at hand. These are the PhDs who experiment with numerous mathematical models and statistical approaches to different problems.

My suggestion would be that, if you are looking for your first internship ever, be open to any role where you write code. However, after your first internship, focus more on finding an internship that allows you to learn and develop AI models.

Recommended plan and resources

Here is my recommended plan with some resources I found incredible helpful. These are listed in order of increasing difficulty, so I’d suggest starting at the top and working your way down!

Pre-req: Know python! https://www.learnpython.org/

Machine Learning Crash Course by Google

https://developers.google.com/machine-learning/crash-course/ml-intro

Great intro class on ML concepts by google (should only take few days to a week to complete)

Step by step walk through of Convolutional NN in Keras:

https://www.datacamp.com/community/tutorials/deep-learning-python

https://www.datacamp.com/community/tutorials/object-detection-guide

Don’t worry if you don’t understand some parts. Just try to pick up as much as possible, and push some code to github!

Intro to machine Learning

https://www.udacity.com/course/intro-to-machine-learning--ud120

This is probably the first more challenging course, but it is extremely informative, and the information is laid out clearly.

Video series of video tutorials on Machine Learning with Python

https://www.youtube.com/watch?v=JcI5Vnw0b2c

Andrew Ng specialization on deep learning and neural networks

https://www.coursera.org/learn/neural-networks-deep-learning https://www.udacity.com/course/deep-learning--ud730

Used creddle.io to redesign your resume to keep it neat

Overall Hyun was extremely satisfied and found value with Vibhav’s mentorship and service by GetCareerAnswers

We are so glad Vibhav was able to provide such amazing career guidance and help Hyun with his challenges and give him the knowledge he needed to reach his goals. It’s so great to know our service is positively impacting the lives of students! It can be especially hard as an international student with financial pressure and the limited time they have to find a company to sponsor their stay in the US. We wish him all the best with pursing software engineering and Artificial Intelligence as a career. With his dedication and drive, I’m sure he’ll succeed. Go get em tiger!! 🐅

Thank you Rohit for this amazing opportunity to connect with experienced individuals. Something that I yearned for whenever I attended on campus Seminars/Workshops, was a chance to have a personal one on one opportunity to ask questions more tailored towards individuals rather than large groups and this service does just that. It really is a wonderful service.

If you’re a student or someone who needs career guidance, sign-up for GetCareerAnswers today. Similarly, if you’re a knowledgeable professional who can mentor to help out, sign-up too!

This is the start to a better future for education.

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Rohit Tigga

Rohit Tigga

On a mission to improve youth mental health. imhereandcare.com

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