Forward-Deployed Engineer, Earth Observation

You will lead deployments of our compression system into real EO workflows. This role spans both sides of the product: making encoding work reliably on constrained hardware (including onboard satellite-class systems), and validating that compressed data remains useful for downstream processing and ML pipelines. You'll work directly with customers and partners, translate operational realities into platform requirements, and help turn early deployments into a repeatable motion. We intend to hire two people into this role profile, with complementary strengths across edge deployment and EO analytics.

• You've shipped EO or imaging ML systems into production, including onboard or edge environments

• You can own integration, debugging, and validation end-to-end across hardware + software

• You've worked with constrained deployments (compute, power, bandwidth, reliability) and performance tradeoffs

• You're comfortable working with customers and shaping technical requirements

• Deploying and hardening the encoder on Jetson / satellite-class hardware

• Integrating our codec into customer pipelines and validating analytics and model utility

• Defining EO evaluation suites that match operational acceptance criteria

• Building deployment playbooks and monitoring hooks that make rollouts repeatable

Salary: $180k–$240k Equity: Founding equity with meaningful ownership Full relocation & visa support

The Compression Company is building the next generation of compression: systems that radically reduce the cost of moving and storing high-value, high-volume data without destroying the information people rely on. We create codecs tailored to specific datasets and deployment environments, and ship them as production-ready encoder/decoder artifacts that run on real hardware - from edge devices to cloud GPUs. We're a small, highly technical team with high ownership and a strong bias toward shipping real systems. We care about measurable performance, strong engineering discipline, and building a platform that compounds with every deployment.