Noah Stein is a seasoned mathematician who recently joined Kintsugi as a Senior Staff Machine Learning Engineer. Noah brings a wealth of experience and a rich background in the realms of audio machine learning and computational research that are instrumental to our mission at Kintsugi.
In his recent tenure at Amazon Alexa, Noah spent over five years as a Senior Applied Scientist, delving into the intricate world of keyword spotting models. His focus on detecting triggers like “Alexa” within Echo user interactions showcased his dedication to refining AI-driven interactions in daily technology.
Prior to his time at Amazon, Noah flourished as a Senior Research Scientist at Analog Devices, Inc., where his pioneering work on audio source separation, aptly termed as “the cocktail party problem,” revolutionized solutions using the world’s first mm-scale microphone array hardware. This invaluable experience in resolving complex audio dilemmas underlines his mastery in the field, setting a precedent for his role here at Kintsugi.
Noah's academic journey is as distinguished as his professional tenure. A PhD graduate of MIT’s Laboratory for Information and Decision Systems, he devoted six years to exploring the mathematical and computational aspects of game theory—a testament to his deep understanding of complex problem-solving paradigms. His foundational studies at Cornell, where he earned a BS in Electrical and Computer Engineering with a minor in applied mathematics, laid the groundwork for his subsequent endeavors.
Currently, Noah is fueled by his passion for neural network modeling in audio applications to sculpt ML software infrastructure that fosters creativity and collaboration among ML scientists, engineers, clinicians, and patients. His dedication to advancing the state of the art aligns seamlessly with Kintsugi’s mission to transform the landscape of mental healthcare and unlocks the opportunity to positively impact millions of people who are currently struggling in silence with mental health conditions.
"Noah joins us at an interesting inflection at Kintsugi as we shape access to mental healthcare to meet patients where they are at. From a machine learning perspective, deploying deep learning models across so many modalities poses both a tremendous challenge and opportunity for our team to define AI/ML deployment best practices in healthcare. Curious and empathetic, Noah is an exciting new leader on our team, and we’re happy to have him here!” – Grace Chang, Founder/CEO Kintsugi
We’re so excited to have you here. Why did you initially consider Kintsugi?
I was drawn to Kintsugi for several reasons. First, the job description specifically called for an 'empathetic leader,' which resonated deeply with my approach to leadership. In technical roles, empathy can sometimes be an afterthought and I wanted to find a space where empathy and technology not only intersect but are actively encouraged. Secondly, the company's mission aligned perfectly with my values, especially in the realm of using technology and AI to scale access to mental health. And least, but certainly not least, as an ML practitioner, the prospect of working with unique data sources, particularly dealing with subjective data labels, intrigued me and the chance to shape the technical direction of the entire ML team felt like the perfect fit for my aspirations.
So far, what has surprised you about Kintsugi?
In my brief time here at Kintsugi, several things have pleasantly surprised me. Despite being a smaller ML team, the amount that they have achieved in a short amount of time is truly remarkable. Furthermore, everyone has been incredibly supportive and responsive, even amidst their busy schedules. I've even found that I've been able to make substantive contributions within just my first few weeks, which is an encouraging start.
What do you hope to learn from your new teammates?
I’m eager to learn a myriad of things from my new teammates. I'm keen to understand the ML techniques that have worked and those that haven't in this unique problem domain. I hope to glean insights from their diverse experiences working on problems different from those I've encountered, exploring how we can apply those ideas here. Additionally, I'm excited to understand how complex ML models, often opaque in nature, can be integrated into the healthcare landscape, and serve as a tool to assist medical experts in the diagnosis, stratification and evaluation of mental health care treatments.
There are so many different opportunities for tech leads to choose from in today’s market, especially with a background as strong as yours. What ultimately made you decide to join the team?
My decision to choose Kintsugi over other options in the market was based on various factors. I firmly believe in the high potential of the technical approach adopted by Kintsugi. The opportunity to apply my expertise in audio ML in a way that can truly make a positive impact excited me greatly. I was seeking a role that combined both individual contributor and leadership elements, as well as a blend of ML science and software infrastructure components. Kintsugi’s philosophy on integrating these roles aligns seamlessly with my own approach and the decision felt easy.
I find joy in playing board and card games, climbing (both as a climber and spectator), and traveling whenever I can. Between my job transitions, I made it to New Zealand, Australia, Hawaii and Kentucky, amongst others, and I developed iOS word puzzle apps called Quintext and Penanagrams, both of which are available in the app store.
Kintsugi is on a mission to scale access to mental healthcare with world-class leaders who represent the makeup of the people we serve. With deep technical and MLE expertise in building and scaling successful products, we are beyond thrilled to have Noah join our team as a thought leader and partner to accelerate our vision for improving access to mental healthcare.
A fast-growing Berkeley-based mental health startup, we are scaling up and hiring for various roles. Check out our Careers Page.