4 minute read
We are proud to have helped hundreds of Researchers take that big leap into their new role. So we thought we’d share some useful pointers on things to consider and how to best prepare for interviews for AI research roles in industry.
But let’s be honest, there are so many avenues to explore… so we’ve put together 8 key points that we believe will serve as a good foundation in guiding your job hunting and interview journey.
1. A Short, Sharp & Succinct CV
A long and dreary CV will no doubt, bore the reader and lead to a fall at the first hurdle.
So, here are some suggestions for your CV:
No more than 2 pages long
List your academic grades
A small collection of your best research papers. *If they’re interested, they’ll hop onto Google Scholar to find out about what else you’ve published*
A link to your Google Scholar
Your technical skills such as programming languages and ML/DL toolkits
Algorithms and models used to carry out your research
The end goal of your research - i.e. what problem you were trying to tackle
2. Brush Up on Applied Statistics and Machine Learning
We’ve found that, especially with PhD Researchers, they have been laser focused on specific methods and models for the past X amount of years. Such as the latest reinforcement learning, multi-agent system or deep learning methods.
So much so (and understandably so), that critical knowledge on applied stats and classical ML is a little rusty.
It might be a good idea to brush up on some models and methods that you studied as an undergrad to avoid uncertainty. There’s nothing worse than having something on the tip of your tongue or ringing a bell and not being sure on what it is.
3. Keeping Up-To-Date
As we all know, the AI-tech industry is not only a huge industry but one that is growing at an accelerating pace. And although it’s impossible to keep up-to-date with absolutely everything within the industry, a good starting point is the latest and most relevant literature within your research discipline and surrounding areas.
As a Research Scientist, you’ll be able to identify top publications online and for free in areas such as computer vision, natural language processing or similar.
Here are some leading conferences where top research groups publish their papers with the latest advancements in your chosen research discipline:
4. Problem Solving Sessions
The majority of industry research interview processes involve problem solving sessions and what they’re interested in: is how you go about this.
It’s easy to feel overwhelmed in these sessions. Racing through your mind is probably all the ways to solve the problem, which you think is best and which they’re expecting you to take.
We could say “don’t worry” but perhaps more constructive advice would be to start with the most straightforward approach. Not all problems will require a Neural Net or RL model, and more often than not the interviewer will prompt you to go further if they are looking for more.
5. Production Coding
Do you ever feel like you’re writing “bloated” code? Think product quality.
Our top tip, although it may sound cliché, is to keep it simple. Run out of the box libraries rather than trying to reinvent the wheel.
6. Start Thinking in a Product Mindset
Ultimately, not all companies have a publication agenda so it’s important to gain perspective in terms of product mindset.
How could your research be useful for product features or platforms? Tech start-ups and scale-ups will want to know how your research and skills could be translated into an applied setting.
7. Shout About Your Experience
All too often, candidates assume that just stating the types of research you’ve been involved in is enough. But, go back and think about all of the prevalent research you have been a part of (or maybe just a few if there’s that many).
Are you able to clearly convey your research experience?
What role did you play in these projects/research?
What challenges did you face and how were they overcome? i.e what did you learn
What aspects did you enjoy most?
Be open and confident about your experience to date: it shows your enthusiasm and engagement.
8. What Are Your Motivations?
You may have felt that throughout your academic career that some research was done for research’s sake, to achieve a publication and there was no real tangible, end goal such as a product or application.
Hiring managers and most definitely founders of tech start-ups and scaleups will be looking for researchers who want to make the world a better or even, more exciting place. To create a real-world impact. For example, using ML algorithms to predict how serious your COVID symptoms are or using AI to build safer, self-driving cars.
We think, this is a good one to end on as in reality, what’s important to you is what really matters!
We hope you’ve found this blog useful and these pointers have either reintroduced some things you may have forgotten about or even shed light on some aspects you perhaps hadn’t thought about before.
Now, could you be one of the many hundreds we’ve helped? If you’d like some more guidance, information or just a quick chat about the things discussed, give us a call!