Machine Learning DevOps Engineer
New York, NY /
Caper builds smart shopping carts powered by deep learning and computer vision to enable a seamless grab-and-go retail experience. We differ from other emerging cashierless technologies like Amazon Go because we are the scalable solution. Caper’s autonomous checkout technology is plug and play, meaning it requires no in-store renovation, no operational overhaul, no heavy computations or endless image labeling. Any retailer can buy the carts and their entire store is upgraded with cashierless capabilities. Caper costs less than 1% of Amazon Go's infrastructure. We are already live in-stores and our customers love us!
Caper is the fastest-growing company in retail automation technology and is backed by Lux Capital, First Round Capital, Y Combinator along with top executives from Google, Walmart, Instacart, Plated, and Albertsons with over $13M in funding to date. While e-commerce accounts for 8% of total retail spending, Caper is innovating the other 92% of the untapped offline retail potential.
As a part of the Caper team, you’ll be a part of a culture that cares about its people and the future we’re shaping together. At Caper, we may all come from different backgrounds, but we all share one common vision - to fundamentally disrupt the retail industry.
Our ML team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term, and we're motivated to make this a great place to work. As a Machine Learning (ML) DevOps engineer, you will be touching new technologies, integrating new tools and creating the new foundations for Computer Vision Research. The core responsibilities of this role include developing and maintaining local server clusters.
You Must have:
- BA in Computer Science or other related subjects.
- 3+ years of software engineering experience in the ML environment.
- Familiarity with basic machine learning and deep learning frameworks such as TensorFlow/Pytorch.
- Familiarity with data systems, pipelines, workflows.
- Familiarity with Docker, K8S.
- Familiarity with Nvidia GPU stack.
- Strong knowledge of computer science fundamentals like Networking, OS, database, data Warehousing.
- Good communication skills and diligence.
You are ready to:
- Participate in infrastructure set up for scalable ML solutions
- Improve productivity of the data science team
- Build and maintain data pipelines and workflows
- Work with a great team and Conquer the World!
- Competitive salary with equity
- Attractive Health, Vision & Dental Plans
- Flexible hybrid work model
- Short Term Disability Plan
- Unlimited Paid Time Off
- Casual work environment