Hi Charles! What’s your job?
As a Machine Learning Engineer, it’s my job to bring ML technology into each block and aspect of our data architecture and product engineering, so that everything we do is state of the art and creating a feedback loop that will inform us on how to continually improve. In tangible terms, we and our users can really see the benefits of ML when it comes to the quality of search results and the speed of using Tactic. What’s even more exciting than that is the new features we’re planning that are built exclusively around ML. We’re a question answering platform so there’s huge scope with what we can, should and will do with ML.
How do you explain the application of machine learning to non-technical people?
I actually recently thought of a very relatable framework! Think of ML as the seasoning and spicing within cookery... You don’t just dump a load of spices on your food after you’ve cooked it all (hopefully!) And your meal isn’t just a pile of salt and cumin, either. That is to say, ML isn’t really a product or technology unto itself until you’re combining it with technology that’s good at doing a specific process. You can implement ML within tech from the very beginning and assess its inclusion and importance at each building stage and module. Maybe it’s more in the background, or maybe it’s more obviously part of the interface that the user uses. But either way, it’s something to combine elegantly with the other ingredients and taste as you go!
Can you unpack how the machine learning elements will create a feedback loop?
Absolutely. Search engines have always been a huge part of how Engineers have been able to learn from users and get a lot of data, so they’re something of a ‘spiritual home’ for machine learning. So, naturally, the more people using Tactic, the better and better it will get because our machine learning systems can read and process the data that people input, the results they want, the answers they pin or dismiss, the data they export and import, and we’ll be able to use all of those signals and the data itself to learn, plan and improve the product. That means re-teaching the machines so that they’re more sophisticated and specialised. It’s very circular, it’s quite a beautiful pattern.
How did you find your way to Tactic?
I’ve always been very interested in startups. I had some startup work experience as a student and loved the environment. As a graduate I actually went a different way though, and worked at a big financial institution for some time. In retrospect I’m glad I did that, even though it wasn’t truly my style, because I was forced to be creative in solving issues that were compounded by big company bureaucracy and red tape, etc. In my mind, when a company is over 3,000 people that’s when innovation really slows down. So I had to figure out a lot of solutions based on these barriers, and it meant that when I came back into the startup world I had quite a wide range of perspectives for problem solving and creativity.
The reason I'm so attracted to startups is that I love what I do in machine learning and more broadly being a computer scientist; but I have other itches too which are quite commercial. So it’s really a bonus for me to be able to witness the commercial side and get excited about what my colleagues are doing in other areas - in a small, energised team you always have access to that. I’m interested in factors that affect product market fit. I’d say at Tactic we’re all quite commercially-minded engineers, and the non-engineers have a real appreciation for the technical side too. So we like to collaborate!
What did you find attractive about Tactic when you applied to work here?
I’ll have a similar answer here to pretty much all the other Engineers, I think: the scale of the problem Tactic is solving is hugely exciting and that motivated me to get on board. Additionally, the way the co-founders wanted to implement machine learning was really smart and not gimmicky. Plus the people, of course! It didn’t take a lot of convincing for me to join.
What are you excited to achieve at Tactic?
One thing I’m particularly excited about is developing a system to provide users with a ‘gold standard answer’ for their questions - a definitive answer - rather than displaying the most relevant snippets and search results (which is already quite a sophisticated bit of engineering!) It will be really special to be able to deliver hard answers.
What’s your best set-up hack, whether that’s your surroundings or your app stack?
I use a shared work space twice a week and so I’ve been perfecting my go-bag! I need a portable second monitor, no compromises. That's number one. I’m also very big into music and rotate through different playlists for different work modes so I need good headphones. And I really enjoy working by a window for daylight and to see the seasons change. I don’t even mind if it causes screen glare. At home I have a window that looks onto a tree, and there’s a little robin living there! It comes and knocks on the window sometimes. Nothing special on the app stack side that I can think of.
Go-to emojis on Slack?
I try to meet the moment with something that shows some good humour, like maybe something that plays on the words of a message. And my fallback would be the cheesy grin! I have a big grinny smile myself so it works. 😄
How do you switch off from work mode in the evenings and weekends?
The biggest way for me is exercise that pulls my mind and body into a very different context. At the moment I’m doing a lot of ju jitsu. I always say there’s no better way for me to switch off worrying about the day’s work than someone literally trying to strangle me! Running or jogging just doesn’t cut it - I need some serious threat level.
If you could work remotely from anywhere in the world for a week, where would it be?
I desperately want to go to Japan. But you know, I’d like to go there and be on holiday. So maybe I’d work by a Portuguese beach or something.
Any work from home rituals?
I like to keep a good routine so that I can be as creative as possible in my work. So I get up and eat at the same time, things like that, and I work out of my spare room or in a shared work space. During the working day I never sit on the couch - that’s how I lose my track for the rest of the day! I separate my spaces according to mindset, and it helps me work hard when I need to and switch off after. And I have a pretty nice ritual too which is going out and buying lunch on Fridays, like I would if I were in an office-based job. A little treat!
Dogs or cats?
Dogs dogs dogs.
Burgers or hot dogs?
Burgers.
Mac or Windows?
Mac.
Slack or Zoom?
Slack.
Film or TV?
Film all the way.
City or countryside?
Countryside, even though I live in the city.
Spring, summer, autumn, winter?
Can I pick spring and autumn? Anything transitional - the scenery looks nicer.
Interested in joining the Tactic team? Check out our open positions here.
