Meet Jeff McGehee: Machine Learning Expert & Very’s Director of Engineering

As director of engineering, Jeff manages all technical delivery at Very. Each discipline – hardware engineering, software development, product design, and data science – has its own subject matter expert oversight, but he is ultimately responsible for delivery of the final product. “Our cohesive delivery process enables team members to work seamlessly across disciplines to deliver Very’s most important product: world-class engineering and design solutions,” he said.

After earning an MS in Mechanical Engineering from Tennessee Technological University, Jeff focused professionally on machine learning in R&D environments. After a couple of years in the field he decided he needed more formal education in computer science, and began a MS in Computer Science from Georgia Institute of Technology with a concentration in machine learning.

In 2015 as he was working on his MS in computer science, Jeff joined Very as a data scientist to further develop his skills with building production machine learning systems. “Consulting seemed like a great way to get a lot of experience,” he said. “And I liked the idea of remote work.”

Pursuing the additional degree while working full-time wasn’t easy. “It was challenging,” he said. “But there was heavy overlap between schoolwork and work projects, so spending the time helped me with both.”

This willingness to roll up his sleeves and put in the hard work is an important principle for Jeff. “In my experience, there are a lot more people with raw talent in the world than there are hard workers. I want to maximize whatever raw talent I do have by ensuring I’m in the group of hard workers and that I’m doing everything I can to reach my goals.”

People-Focused Problem Solving

As an engineering leader responsible for high visibility consulting, Jeff spends most of his time focused on people’s needs rather than technical minutiae. Very delivers premium, highly customized, and fast-paced engagements that require clear communication dynamics across disciplines and daily interactions with customers. “We have to be masters at setting expectations and leaving the customer with the impression that we are the best team they could have chosen to solve their problem,” he said.

For Jeff, applying this people-focused approach to his internal teams means playing the long game. “There’s not an expectation that you know everything, but there is an expectation that you will learn over time and avoid repeating your mistakes,” he said. To support engineers’ ongoing development and success, every project team includes tech leads who serve as mentors and facilitate relationships within and across disciplines. This system allows each team member access to knowledge and experience from anywhere within the organization.

Learn. Teach. Repeat

Outside of Very, Jeff regularly speaks about IoT development best practices at national events, such as MLconf and IoT World. He holds a patent for developing machine learning methods for calibrating color sensing devices, and while in academia, published research centered around applied machine learning for hybrid vehicle control systems.

His commitment to humility and lifelong learning has served Jeff well as an engineering leader and in his personal life. He spends his downtime in a “general pursuit of assuaging my intolerance for relying on technology that I do not understand,” he jokes. Sometimes that takes the form of tinkering in his friend’s auto garage (if replacing an entire engine counts as “tinkering”) and other times focusing on his most challenging and rewarding project to date: his children Henry and Madeline Jane.

If you’d like to join Very and be part of Jeff’s team, apply to one of our open roles. We’d love to talk.