The Company:
Descartes Labs is a geospatial intelligence company with science and technology at its core. Launching out of Los Alamos National Laboratory in 2014, we build models of the earth to power the analysis of the world's largest physical systems. Our data science and software solutions create new sources of operational advantage for Agriculture, Consumer Packaged Goods, Mining, and Government. Descartes Labs is proud to be a remote-first, deliberately distributed organization that recognizes that people have different needs and motivations for building a life and career that matters and works for them. For this reason, we are open to our employees working from any location, in a way that enhances their well-being, productivity, and role. We focus on helping our employees produce positive outcomes and we recognize that the path to getting there will look different for different people.
The Role:
As a Machine Learning Infrastructure Engineer, you are responsible for engineering patterns for producing production-ready models and creating and maintaining our infrastructure for data science work. This includes cloud resources such as databases, clusters, and storage. This also includes infrastructure that doesn’t yet exist such as model training / serving platforms for Applied Scientists developing models.
You belong here! Nobody checks every box and if your experience and interests match some of the above, we want you to apply.
Descartes Labs is committed to building a diverse community, where employees feel they belong, even if they are different. Scientific discovery is in our DNA and the more inclusive we are, the better our work will be; diversity fuels innovation!
Accommodations will be provided as requested by candidates during all aspects of our interview process.