Paperspace is a leading provider of high-performance cloud computing. We offer a range of products powering everything from virtual desktops for businesses to deep learning pipelines for individual developers, startups, and enterprises.
Paperspace Gradient, is a high-performance, cloud-based machine learning operations (MLOps) platform that enables AI teams to accelerate and scale the development and deployment of production-ready deep learning models. Gradient’s development environment supports building and training models with Jupyter notebooks, Python command line, and the Gradient web interface. It provides cloud-agnostic support for end-to-end deep learning model development, management, and deployment.
Keep brilliant people around, and their insights will enrich not only our products but our company’s culture as well.
We’re working at the frontlines of the infrastructure powering the A.I. revolution. Given what’s at stake in the development of these tools, we need to do things a bit differently than more established players.
We’re doing something most would consider counter-intuitive to our short term interests as a high-velocity startup. But to us, the long-term implications of these tools don’t give us a choice but to counter traditional startup models and fund a pure, in-house research division.
Academic breakthroughs in ML/AI often outpace those stemming from professional contexts. The ATG Research Fellowship bridges this gap, engaging Paperspace engineers with some of the brightest minds in ML/AI research.
The ATG Research Fellowship is a structured, collaborative environment in which the company and core products benefit from the cutting edge insights of academia. The group is tasked with exploring advanced topics in machine learning, data engineering, and UI/UX for Intelligent applications.
The Research Fellowship is a 10-15 week paid program that is designed to bring in Graduate and post-Graduate students from a wide variety of disciplines who want to apply their passion for research in a practical setting.
Researchers-in-residence gain practical experience, but retain total autonomy to pursue their interests, while making the most of Paperspace’s products and expertise. They are paired with a Paperspace engineer who assists, advances and documents their project.