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.

We need a cleared geospatial data engineer with strong experience building processing pipelines and familiarity with earth observation data. This role will help us build our cloud based supercomputer that currently ingests 10 Terabytes of near real-time geospatial data per day within the requirements of our Federal partners. Our microservices-based platform is developed from the ground up cloud-native, and we see a peak load of nearly billion API calls a day. We aim to supercharge machine learning scientists to ask geospatial and temporal questions not previously possible to understand the changing physical world better.

Your Impact

• Keep our data ingest and processing pipelines up-and-running within security parameters of federal partners in classified and unclassified environments
• Make our data storage and access faster and more scalable
• Work with our science team to build a system that allows them to focus on analysis
• Contribute your own ideas to our machine learning team

What You Bring

• Undergraduate degree in a relevant technical area
• Strong familiarity with Linux systems
• Real-world software experience in Python is required; experience in other languages is also valuable
• Proficiency with git and modern distributed version control system practices is required
• Code examples (preferably on github / bitbucket / etc) are required
• Familiarity with cloud systems (AWS/Google Cloud) and cloud infrastructure is a plus
• Experience with high performance or large scale computing infrastructure
• Experience with geospatial, planetary, or astronomical datasets is valuable
• Existing Secret, TS preferred clearance

Our Interview Process

• Qualified candidates will be invited to schedule a 45-minute interview with one of our recruiters
• Depending on the outcome of the recruiting interview, candidates will be invited to schedule a 30-60 minute interview with our Engineering Hiring Manager
• After that, candidates will be invited to schedule an additional 30-60 minute technical interview with an additional member of our Engineering team
• Finally, candidates are invited to a final round of virtual interviews with ~5 members of the Technical team

Top Reasons To Work At Descartes Labs

• We pride collaboration over ownership, iteration over perfection, principles over rules, and discussion over directives
• We’re using the world’s top technology to solve the world’s largest problems with a strong focus on sustainability, environment, and impact science
• We look at Descartes Labs as a work environment where people are included, treat their colleagues with professional regard and respect, and thrive as a result
• We’re a highly collaborative company that constantly promotes success through teamwork
• We strongly encourage and enjoy a flexible work environment
• Descartes Labs offers a generous compensation package including a competitive salary; choice of medical plan; dental, life, and disability insurance; a 401K plan; paid holidays and flexible paid time off

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.