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.
As a successful 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!
As a principal engineer you will help set the standard for how we do machine learning at Standard, and will have a front seat at designing our technical roadmap for how we achieve our most ambitious company goals.
This is a FULL TIME remote role located anywhere in the United States or the European Union.
What you'll do here:
Contribute to the end to end development of state of the art machine learning systems, from metric definition and data set creation to model deployment and monitoring Solve modeling problems at the cutting edge of production machine learning Mentor ML project teams, providing guidance on approach, model design, and production best practices Work cross-functionally with operation teams in data creation and labeling to help design our massive data sets Design and deploy monitoring, profiling, and instrumentation for the models you work on Build data processing pipelines, training pipelines, and hard example mining systems from production data streams
Your skillset:
-4+ years of experience building production ML or CV systems -6+ years of total engineering experience or 4+ years with a PhD in CS/Math/Physics -Proficient in Python -Proficient in at least one systems language such as Rust, C++, or Java (we use Rust!) -Experience with cloud build, deployment, and orchestration tools -Experience with MLOps tools such as MLFlow, KubeFlow, Airflow, or Dataflow -You communicate clearly and possess the ability to work cross-functionally across team boundaries -You are able to problem solve in a flexible manner -You are passionate about the entire ML lifecycle
Only meet some of these traits or experiences? We'd still love to hear from you!
Why you might want to work with us:
-We take care of you and your family with health, vision, and dental insurance. -You will have the option to contribute to a 401k. -You're excited to work on a product that will impact almost any consumer, almost anywhere. -Standard is a remote first company. We trust you to get your job done in the location that works best for you. -We dress casually. Some of us wear slippers in the office. In current work from home standings, we’re super comfy. -We believe in a culture of learning, and want to keep building our skills, experiences, and capabilities. -We offer flexible work schedules. We trust our team to know how they will do their best work. -We're family friendly. We want our teammates to focus on what they need to when they need to. -We offer very competitive compensation, including equity in Standard, to each one of our employees.
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.