Lambda

Lambda has been profitable for a few years providing GPU servers and workstations for training of neural networks. Our customers are ML researchers and engineers who already have trust in our products, and have now created a demand for Lambda to provide cloud infrastructure as well. Thus, our software engineering team is still very early and small, consisting of our founder and 2 engineers. Anyone we hire at this stage will have a direct impact in guiding our software development product and process evolution. Some aspects of our engineering environment are: * Highly autonomous * Small team which values the sophistication of simplicity * Everyone has ownership of their code through production * High expectations for quality code * Deploy to production multiple times a day * Very light code review currently, but moving more toward code review model as we scale

We’re building GPU cloud infrastructure for targeted ML communities, with extremely high networking bandwidth (north of 800GB per second). Imagine building the ML infrastructure for an eventual Facebook Learner (FB's ML Infra) or similar ML platform at scale in its early days. Each of our software engineers will build reliable, scalable, highly available systems, and be responsible for the entire stack in developing ML Infrastructure Management software used directly by our customers - the industry's foremost ML and Deep Learning professionals.