Machine Learning is a critical piece to process the huge amount of imagery we acquire at scale. In that context, the machine learning team is dedicated to extracting quantifiable information from nationwide ultra-high-resolution imagery leveraging the vast geospatial database that EagleView has built over the last 10 years. We combine our one-of-a-kind data, our cloud-base ML pipeline, and the latest Deep Learning and Computer Vision research to improve existing products and create new ones.
We are looking for a Software Engineer II to join the Machine Learning team and work on developing cloud infrastructure to deploy Deep Learning models at scale. This is a multi-disciplinary role that requires a solid foundation of software development, distributed systems and some background in Machine Learning or Computer Vision.

Primary Responsibilities

• Develop inference pipeline code to deploy Deep Learning models in the cloud.
• Help design cloud orchestration architecture.
• Collaborate with Data Scientists and other engineering teams to ensure proper alignment.
• Participate in agile practices with the rest of the ML team.

• Strong python or go experience.
• 2+ years of Software Engineering experience
• Knowledge of CI/CD practices with tools like Jenkins, ArgoCD, etc.
• Experience with at least one of the following: container orchestration, distributed systems, computer vision or image processing pipelines, machine learning pipelines, photogrammetry/GIS problems.

Nice to have

• Experience designing REST APIs.
• Some understanding of Deep Learning/Machine Learning.