As an application engineer Hugo gets to work across a huge variety of areas. In the past year, he's worked on projects covering iris recognition, interest rate forecasting, formula one telemetry, smart energy systems, radar tracking and banking regulation.
What’s your name?
Where do you work?
MathWorks, Cambridge, UK.
What's your job title?
Application engineer (maths, statistics and optimisation).
How long have you been doing that?
Just over a year.
How did you get there?
I studied electrical engineering and computer science at Imperial College London, and spent my master’s year in Paris on an Erasmus exchange programme studying image processing and artificial intelligence. When I came back to the UK I enrolled in a PhD programme at Imperial, studying multi agent systems and machine learning techniques.
What's the work and day-to-day experience like?
Application engineers at MathWorks act as pre-sales consultants, speaking to customers about their technical problems and framing solutions in the context of MATLAB and Simulink.
Primarily, it’s up to us to identify what tools and services a customer needs to solve a problem, and support them during evaluation periods of the software. This can involve customer meetings, customised proofs of concept, and seminars which demonstrate how different tools can be applied.
What's the best thing about the job?
The variety of application areas is astounding. In the past year I’ve worked on projects in iris recognition, interest rate forecasting, formula one telemetry, smart energy systems, radar tracking, and banking regulation. It’s been amazing to see how many industrial applications are underpinned with MathWorks products.
And the worst?
Despite being one of the things I enjoy most about the job, the variety of application areas is staggering, and it can be a bit daunting to talk to so many different companies every day.
A challenging part of the job is often filtering out the industry specific jargon from the conversation in order to gauge what the most important parts of a given problem are.
What standout things have you got involved in?
Several of my priority accounts have been investment banks and hedge funds, as well as the UK financial regulators. It’s been fascinating to see life in this sector over the past year from both sides of the coin (so to speak).
How would you describe life as a working engineer?
Every day is a new challenge, and you never know what’s going to land in your inbox.
Fortunately MathWorks has an extensive support network of international application engineers and developers who are always there to give advice and help point you in the right direction. You learn pretty quickly what you don’t know and how to assemble streams of information in a coherent manner.
As an employer, MathWorks invests heavily in staff development so I am always learning and there are plenty of opportunities to work on exciting and challenging projects.
What did you expect when you started work? Was it what you expected or did anything surprise you?
When I joined the MathWorks, I didn’t expect to use all aspects of my degrees, but have had to call on almost everything I’ve ever studied just to keep up. I didn’t think I’d have to dig out my signal processing and control theory notes for a meeting with an insurance company!
Is there any advice you’d like to pass on to those about to enter an engineering workplace?
As we move into a data-oriented world, industry is becoming increasingly desperate for science and engineering students with strong maths backgrounds. My advice would be to put your maths and programming skills front and centre, as they will leave you in a great position during the application process, and ultimately make your CV appropriate for a broader range of jobs.
What do you think you'll do next?
Application engineers at the MathWorks initially see a wide range of industries and applications but go on to specialise in one or two preferred areas. Over the next couple of years I’ll be looking to deepen my technical skills with some larger projects in the areas of data analysis and statistical modelling.