Orbital Sidekick (OSK) is revolutionizing how the world understands and interacts with our planet. We are the leading hyperspectral satellite data and analytics company building the most advanced space-based infrastructure and proprietary "Spectral Intelligence™" platform. Our constellation of Global Hyperspectral Observation Satellites (GHOSt™) delivers unparalleled, persistent monitoring capabilities, capturing an unparalleled 500 bands of light to reveal the chemical fingerprints of targets on Earth. We provide actionable insights to critical sectors including Energy, Mining, Agriculture & Forestry, Environmental & Emergency Monitoring, and Defense & Security, helping our clients optimize sustainable operations, mitigate risk, and enhance situational awareness globally.

We're seeking an Applied Machine Learning Engineer who thrives at the intersection of theory and practice. You'll operate as both an applied scientist and systems builder, taking end-to-end ownership of ML solutions. We're looking for someone who can spot inefficiencies, architect solutions, and build the tools needed to scale our capabilities.

This role is perfect for builders who are equally comfortable diving into ML theory, developing internal tools from scratch, and architecting production pipelines. You'll have the autonomy to identify gaps, propose solutions, and drive them to completion in a fast-moving startup environment.