Patrick Hayes is Co-founder and VP of Engineering at SigOpt. Patrick has been working at tech companies both large and small for over 8 years. At SigOpt, he leads the R&D team where SigOpt is building some of the most cutting-edge mathematical optimization techniques in the world. He has a Bachelor’s degree in Mathematics from the University of Waterloo.
How did you get into the industry?
I started writing code when I was in middle school. When I went to the University of Waterloo to study Mathematics, I was involved in their outstanding co-op program where I did six internships at different tech companies, which is what got me started professionally in the industry. After that I was an engineer at Foursquare, working on their passive awareness notifications that would alert users to the best content nearby. Now I’m at SigOpt leading the R&D team.
Any emerging industry trends?
AI and Machine Learning are becoming more and more entrenched into everyday technologies. The number of jobs that humans are better at than computers shrinks every day. It’s becoming clear that if you’re not investing in Machine Learning, you’re missing out on a huge opportunity for your company. Model tuning and optimization is a great opportunity for businesses to take the Machine Learning they’re already doing, and improve its accuracy and decrease its costs.
Any industry opportunities or challenges?
Machine Learning isn’t a magic bullet – doing it right (and knowing when to use it) requires a lot of resources and expertise. And there are huge costs to doing it wrong. So companies are going to be investing a lot of money and infrastructure into improving their Machine Learning capabilities in the coming years. Services like SigOpt that let you make better models with less expensive research time are a huge opportunity.
Inspiration for the business idea, and your vision for the Business?
My cofounder and I saw that R&D experts all over the world (in academia and in business) were wasting time optimizing their products by manual trial and error. We built SigOpt to help our customers make better models with fewer resources and less research time. Our goal is to make experts in every field more efficient, whether they are building Machine Learning models, making financial trading algorithms, or even brewing beer. We want to democratize the cutting-edge research behind SigOpt, and make it so easy to use that every R&D department in the world has access to it.
Your key initiatives for the success of the Business?
I developed the first version of our optimization platform, which made it easy for customers to access the cutting-edge research behind SigOpt, and working on scaling it to support our growing customer base. We took the powerful research that was locked up in academia, and exposed it as a web service that anyone can use. I now work with a team of brilliant engineers and mathematicians to make that platform even easier to use, and to enable us to tackle problems of new types.
Your most difficult moment at the Business? (and what did you learn?)
When we founded the company and were going through Y Combinator. The company was just getting started and nothing was built yet. My cofounder and I were working all hours to build out the product and get customers. I learned a huge amount by being forced to work on all parts of the business – sales, marketing, design, hiring. Working on things you are bad at is a great way to learn
Ideal experience for a customer/client?
Our job is to enable our customers to be great at what they do, instead of trying to do it for them. That’s why we want our customers to be able to get started with SigOpt immediately, so we make our service as easy to use as possible. Our customers are able to get started with our website and API in minutes, so that they can spend their time focused on their own domain expertise, which gets amplified by SigOpt.
How do you motivate others?
Give people autonomy and ownership. Hire people you trust to execute on your company’s vision and then let them do the rest.
Career advice to those in your industry?
Expose yourself to as many different technologies as you can. Learn new languages and work in new fields. As your career progresses, individual technologies will come and go. But a breadth of experience that enables you to get up and running in an unknown environment is always valuable.