At Meta, Michael Vaks ’19 helps solve the engineering problems behind an everyday expectation: a device should respond when someone needs it. As a staff software engineer on the company’s Core UX / System UX team, he builds foundational software for wearable devices, including AI and display glasses.
At NJIT, Vaks studied computer science and applied mathematics as a scholarship recipient through the Albert Dorman Honors College.
Don't be afraid to take on projects involving technologies you're unfamiliar with.
His campus involvement included the social fraternity Pi Kappa Phi and the professional business fraternity Alpha Kappa Psi. He also contributed articles to NJIT’s student newspaper The Vector, participated in a campus hackathon and served as a teaching assistant for an introductory computer science course one summer.
While studying, Vaks worked at S&A Technology in NJIT’s Enterprise Development Center and completed internships at Goldman Sachs and Facebook. Two internships at Facebook led to a full-time position after graduation.
In this Q&A, Vaks discusses the engineering behind wearables, how AI could fit into daily life and the hands-on experience that helped prepare him for his career.
What does your role at Meta involve, and can you share an example of your work on wearable devices?
As a staff software engineer on Meta’s Core UX / System UX team, I help design and build the foundational software systems and user experiences that power our wearable devices, including AI and Display glasses and emerging products in the wearables space. My work spans Android OS, real-time operating systems, system applications and the frameworks that support core device functionality and user interactions. This includes designing software architecture, developing new system-level capabilities, and improving performance, reliability and efficiency.
One example is helping architect a modular, persistent system interface that supports the device's core interactions. By decentralizing components that are traditionally tightly coupled within Android, we built a more efficient architecture better suited to the hardware constraints of wearable devices. This reduced communication latency from hundreds of milliseconds to under 10 milliseconds, freed up over 60 MB of memory, and made it easier to upgrade to newer Android versions without reworking as much of the underlying system.
What is one engineering challenge you’ve encountered when bringing AI to a device people wear or carry, and how did your team approach it?
One of the biggest challenges is delivering a responsive and reliable experience within the hardware constraints of a wearable device. Unlike smartphones, wearables have much tighter limitations around processing power, memory, battery life, and heat. Part of our approach involves carefully managing where and when computation happens, including offloading certain workloads to more power-efficient processors, reducing unnecessary background processing, and optimizing resource usage throughout the system.
What do you see as the most meaningful change wearable devices could bring to the way people interact with AI?
I think the biggest opportunity with AI in wearables is providing a more accessible and natural way to interact with it throughout the day. Today, using AI typically involves pulling out your phone, opening an app, and looking at a screen. With wearable devices, there's an opportunity to make those interactions more immediate and less dependent on traditional interfaces. We see this today with the ability to instantly ask AI about our surroundings while wearing a pair of Meta Ray-Bans.
What will be most important for AI wearables to become something people find useful and trust in everyday life?
These devices need to solve real problems and work consistently enough that people can depend on them. People also need to feel confident about their privacy and have control over how their information is used. Ultimately, the technology should make everyday life easier without demanding more of our attention.
What experience at NJIT helped shape your career?
One of the most valuable experiences I had at NJIT was working at S&A Technology, located in NJIT's Enterprise Development Center (EDC). I worked on a wide range of projects across different industries, from developing a system that improved the efficiency of 3D printing parts for the U.S. Army to rebuilding API functionality that saved Coldwell Banker approximately $50,000 annually in licensing fees. I even worked on and helped field test augmented reality training applications and software projects for massive companies like Bayer and Skanska.
What advice would you give NJIT students interested in a similar career?
Get as much hands-on experience as you can while you're still in school. Internships, part-time jobs, personal projects, and even hackathons are great opportunities to apply what you're learning and figure out what interests you. Don't be afraid to take on projects involving technologies you're unfamiliar with. Some of the most valuable experience comes from figuring things out as you go.
