- New York, NY, United States
Paperspace is looking for highly motivated engineers to help us architect the future of machine learning and GPU cloud computing. This position requires a love of software and a willingness to jump between many levels of a stack (from nitty gritty optimization to questions of systems architecture and organization).
The ideal candidate should be interested in new tech/frameworks/tools but more importantly should be willing to do whatever is most expedient to get the job done.
Excellent communication skills are essential.
- production deployment / DevOps experience (Docker, Kubernetes, CI/CD, etc)
- experience building and extending backend server frameworks
- familiarity with microservices architecture and design patterns
- SQL and NoSQL datasource experience, including schema design/data definition
- Git/GitHub experience, including merging, rebasing, and pull requests
- Technical leadership experience is also desirable but not required
Paperspace provides an elegant GPU compute platform designed to eliminate infrastructure bottlenecks for developers.
Our Gradient product is CI/CD for Machine Learning: A popular toolkit for developing and deploying Deep Learning models. Teams of all sizes use Gradient to iterate faster and collaborate on intelligent, realtime prediction engines.
Paperspace is backed by leading investors including Y Combinator, Initialized Capital and Data Collective.
Our mission is to make cloud computing more accessible through radical simplicity, community-driven technical resources, and straightforward pricing.
Our culture is open, respectful, and flexible. Everyone is passionate about being on the team and making a huge impact though our efforts. We challenge each other when needed, but we don't have a hierarchy of people who know more, and those that know less. We respect everyone's opinions, especially during the planning process, and we encourage everyone to contribute. We also enjoy socializing after a major release, or sometimes just having a random lunch all together. Our environment is very informal. You will see that we care as much about each other as we do our product.
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