The earliest research in the field of artificial intelligence began 60 years ago, originating with a project at a conference at Dartmouth College in the summer of 1956. Since then, AI’s earliest pioneers and modern researchers alike have been working to create smarter, more autonomous systems, from AI written screenplays to Google Assistant.
In New York City, a number of startups are entering the rapidly developing AI industry, which is still largely unchartered. We caught up with two experts working in this space to find out what it’s really like to work for a company centered around artificial intelligence.
Jeff Smith is a Data Engineering Lead at x.ai, which provides virtual personal scheduling assistants.
Ian Jaffrey is a co-founder at Wade and Wendy, which is using AI to create virtual recruiting assistants
Built In: Can you describe the employee culture at your company?
Jeff Smith: It's an environment of some very smart people, who challenge each other to rise to the challenge we've signed up for. The baseline for that is mutual respect and trust that your teammates can and will do awesome work on problems that people haven't solved before. But it goes beyond that to an expectation of continual learning and growth. Our data scientists are expected to learn how to write production-grade, well-tested and functional Scala code. Our data engineers are expected to learn how NLP, ML, AI and related fields work in a way that allows them to be equal contributors to our modeling infrastructure. So, then that all comes together in a culture where we are all constantly trying to find ways to teach each other and support each other's growth. We try to create conditions that enable team members to do their best work and be the best contributor they can be.
Ian Jaffrey: Humble, collaborative, curious and eager to learn. The team is also very multi-disciplinary. We're venturing into an emerging area of AI that's highly complex, so it requires a coordinated effort from several domains to realize our vision.
BI: What projects and goals is your company currently working on?
JS: A lot of what he have to do right now is based around doing fundamental data science research in such a way that we can broadly explore various techniques and rapidly productionize the successful ones. We're pushing the boundaries of what is possible in so many areas; we can't just download pre-built libraries and models we need off of the internet. We're trying to build an AI that can read and understand emails about meetings better than anything ever has before, so we need to be able to go from an idea to a production implementation, that can operate reliably at scale. That’s how we can prove out that a given idea can enable the sort of intelligence we're aiming to build.
IJ: A big goal for us is developing a great conversational user experience. There are a lot of nuances involved, as unstructured text presents many inherent challenges. We want conversations to be engaging and fun, and we're working on giving both Wade and Wendy distinct personalities. This is a completely new approach for the HR and recruiting space, so it's an exciting challenge to pioneer.
BI: What do you look for when hiring new employees?
JS: Our pledge does a good job of summing this up, but here's some more color. We are looking for people who want to learn and grow into the person who can solve a problem that no one else has ever solved before. At the same time, we're looking for people who are already awesome at things like functional programming, distributed systems, machine learning, etc. That's a prerequisite for our highly autonomous approach to letting small teams of smart people determine their own destiny. But it's really important for people to come in with that expectation that they will be taking on things that they've never worked on before. People who excel here really relish the challenge and opportunity that our unique situation has to offer, and they're not afraid of the wild, untamed nature of how complex of a problem we're trying to solve completely.
IJ: From a culture fit perspective, we're looking for people who align with our values. Empathy is critical as everything we work on is grounded in a human-first mentality. We also look for people who are curious and driven to learn, as we're all striving to improve ourselves and be the best at what we do. Lastly, I'd say we appreciate humble and collaborative dispositions. To achieve our vision it will truly take a multidisciplinary effort and we all need to support each other.
BI: On a day to day basis, what are your responsibilities and priorities?
IJ: I would say our day to day responsibilities and priorities are quite multidisciplinary in nature. We're passionate about creating great conversation, organizational design, career development, and innovative technology to power a novel approach for the HR and recruiting space. We're not just about completing transactional tasks; we're aiming to develop trusted relationships between our AIs and users. To accomplish this vision, we're creating a robust technical platform, implementing a lot of machine learning and natural language processing techniques, developing characters with personality, and layering in domain knowledge around functional areas (e.g., product management, data science, software engineering). In this early stage I spend a lot of my time across functions—operations, building our team, and sprint planning. I also play bartender for our weekly Old Fashioned Fridays.
BI: What is your favorite part of working for your company?
JS: I love the people here. People are all that matter to a company like ours. That's why we care so much about finding truly awesome people and investing in their growth. I come to work every day, and I don't have the answers to all sorts of things that are going to crop up in my day. Often enough these are questions that would stump the Google search box, AI experts, and really everyone else. But I work with a ridiculously talented group of people who are masters in the art of taming the unknowable, so I get to lean on them and collaboratively discover how an AI can be built to completely solve the problem of scheduling meetings. That's what I love about x.ai.
