My co-founder and I were working in the online learning division for a large global publisher, helping launch new degree programs for people seeking jobs in emerging industries like energy, advanced manufacturing, and personalized medicine. Through that process, we found that these organizations doing workforce development don’t have enough insight on these new fields to help connect people with the right jobs. We saw an opportunity to close that gap and started Julius Education.Simply put, we’re a workforce technology that helps communities, organizations, and job-seekers navigate jobs of the future. We do two things: One, we generate new labor market data for customers like federal agencies, state workforce agencies, trade associations, and large employers, who are all aiming to build better performing workforces. And two, we build that information into tools for job-seekers.
Massachusetts is a great example. The state wants to move toward a net-zero grid and needs help mobilizing interest and talent in the sector to support that effort. Since the roles involved in creating a net-zero grid are often unclear, we built a career map that identifies entry, mid-level, and senior positions—jobs like installing solar, utility work, grid construction, and battery storage. Our tool helps demystify what a "net-zero grid career" means and introduces people to all these opportunities across the sector.
The core of our work is gathering data. We use AI to parse every job posting in the country and then organize them with great precision. Employers describe these jobs in so many different ways, so we use all the information in a job posting to determine if they’re the same or different—essentially standardizing the listings. As a result, we can glean much more accurate data about these industries. We did a lot of pilots to sort through these challenges from day one, but the Google for Startups AI Academy: American Infrastructure program really accelerated our ability to build effective classification models.