At Standard Cognition, we’re revolutionizing the way the world shops. By replacing cash registers with computer vision-powered checkout, we’re creating a frictionless experience for shoppers. Since launching in 2017, Standard has contracts with multiple global retailers and is in the process of deploying our Standard Checkout solution across thousands of stores globally. We’re backed by some of Silicon Valley’s leading investors including Softbank, CRV, Initialized, EQT, Draper Associates and YCombinator. We just announced our Series C in February 2021!
We’re building a soft real-time machine learning system that provides shoppers with a seamless checkout experience. Our system is vision only, and every store must stream process terabytes of video per day from hundreds of cameras, touching on a multitude of interconnected models. We’re pushing the limits of what video comprehension can achieve, and we’re expanding to do it at scale. You’ll be helping us solve problems that few teams have ever tackled.
We use techniques from both ML and Deep Learning, and merge them with powerful approaches from applied graph theory, combinatorics, and optimization theory. Collectively, we create state of the art systems that can visually track visitors and their actions across the most challenging real world multi-camera environments, without ever relying on facial recognition.
As a successful Machine Learning Engineer (MLE) at Standard, you will design and build high-quality production inference systems that drive key impacts to our core business. All our ML Engineers contribute to the full life cycle of model development, from cross-functional data set acquisition, to training pipelines, to model design, to scaling out model serving and monitoring. If this sounds like fun, we’d love to hear from you!
This is a FULL TIME remote role located anywhere in the United States or the European Union.
Standard provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.
Not quite ready to apply? Send us an email at email@example.com. Someone from the team will follow up to answer your questions.
Improving the retail checkout experience, by removing it entirely.