My name’s Eddie and I work for DS Group where I specialise in recruiting Machine Learning Engineers. I have to be honest, I have only been in this role for just about 2 months and I must say, based on previous experience in recruitment, it’s completely different working within the tech industry! Who knew the market could be so niche and with so much to learn about what it is these Engineers do on a day-to-day?!
It’s for these reasons I decided to venture out to some Tech Leads and CTOs of start-ups to try and better my understanding of the market. I wanted to start by asking what they think the top three skills a Machine Learning Engineer should have to make it in such a niche market, or better yet, what three skills they would like to see in the ML engineers who join their team. I also wanted to find out what they thought were the current trends within the industry.
So without further ado, here’s what they all thought:
Barrie Roche – CTO at Lucid House
In the eyes of Mr Barrie Roche, the perfect ML Engineer needs to be:
1. Know Python!
He feels that Engineers that are new to the industry need to know Python inside and out as this is what drives them to code in new languages - there ain’t nothing wrong with good ol’ Python!
2. Data, Data and Data
A good Engineer should be able to create their own data. It’s all about understanding the commercial world and knowing the ratio of speed and value.
3. Understand the Customer’s Journey
It’s not just about how fast you can write a quality bit of code, but also obtaining the ability to see that problems aren’t always solved by throwing some Data Science at it. Take time to understand the customer and their journey.
Now…onto Barrie’s thoughts on current trends, let’s keep this bit short and sweet:
Cloud based IPU Processes
João Leal – Co-Founder & Head of AI at Screenloop
João’s thoughts on what makes a Good ML Engineer:
1. Research & Production
Someone that is able to understand a high level of ‘state of the art’ research and bring it into production.
2. Product Sensibility & Problem Solving
It’s important to have product sensibility. Machine Learning is rather new, so someone that’s keeping up-to-date with the market is essential. And, be able to provide solutions to problems: with the ability to discuss in detail.
It’s beneficial to understand that some problems are easily solved with public programmes such as AWS and that it isn’t completely necessary to build in house.
João’s thoughts on trends:
GANS – lots of cool stuff happening at the moment.
Fraud and anti-spoofing mechanisms
Lawrence Lilley – CTO at Mutual Vision
Now onto my discussion with Lawrence Lilley’s top 3 skills:
1. Public Cloud - Azure Sentinel
They need to know how to use and actually use it and understand it. On top of this, someone that knows how to run the public cloud – it’s here to stay!
2. Processing Large Data
This is super useful when it comes to Data Analytics.
3. Using Language Everyone Knows
Process data in languages that are commonly used so nothing’s too difficult to find.
*One of Lawrence’s Pet Peeves* Having to get up at 3am to fix a problem but it takes hours as the code is written in a way he’s unfamiliar - he likes to use Python mainly as everyone can use it.
Now, Lawrence’s views on current trends is slightly different. He feels that the main trend in tech is that candidates have extremely high expectations in salary. Over the last 18 months Lawrence thinks that the salary expectations have doubled which has made it a bit tricky in finding new employees.
Matt James – Director of Data Science and AI at DRCJ
Here’s what Matt had to say:
1. Understand the Problem
The ability to understand the problem that has been put in front of them, what the specific model is doing and why you have chosen that model – interpret the model to your utmost.
2. Know Your Field!
Have the knowledge of what is happing in your specific Engineering field and know what is relevant and what’s not.
3. Big Data
A crucial skill to have – for sure!
And finally, Matt’s thoughts on current trends:
GANS (It must be popular to come up twice!)
Looking back on what everyone has said and after being in this market for just about 2 months, I think they have all made some really relevant points on what to look for, I really like that its not a bad thing to keep things simple in this field. I also say simplicity is key!
After reaching out to so many people within tech I feel like it has really opened up my mind to a lot of things. Especially being a recruiter in this market, researching for this article and taught me what to look for when finding ML Engineers for my clients. Just another brick down on my path to being the best tech recruiter possible!
Lucid House: They have created a smart meter to monitor your home and energy bills, with an app on your smart phone to keep track of what you are spending.
If you would like to know more, check out their website: https://www.lucid.house/
Screenloop: This company uses AI to build a system for recruiting, sourcing and interviewing! It is their mission to empower businesses to do these things with ease and at scale!
Check out the site here: https://www.screenloop.com/
Mutual Vision: Using open technology to connect their customers to intermediaries, suppliers, FinTechs and consumers. They are the digital platform provider of choice for Building Society and small bank sector delivering highly effective and affordable core banking and digital front-end solutions whilst exercising ethical business practices.
Find out more here: https://www.mutualvision.co.uk/
DRCJ: Their clients create value from waste and with circular process design. Their particular interest lies in generating renewable energy from industrial processes and in waste management.
You can check out more here: https://drcj.co.uk/