About the role

Muon Space is building a family of infrared imaging missions designed for global wildfire detection and monitoring, weather and cloud characterization, space-based environmental monitoring, and more. Muon's IR Data Products team builds the analytics system that turns raw imagery from our spacecraft's custom multispectral instruments into calibrated, orthorectified, analysis-ready products — and delivers them fast enough to be useful while a fire is still burning.

In this role you will build and operate the production pipeline that does this. Our system ingests raw frames from orbit, calibrates and geolocates them, orthorectifies them into map-projected tiles, and derives fire detections and perimeters — all under a hard latency budget, and increasingly on a continuous basis across a growing constellation.

This is hands-on production software engineering on a system with real users and real deadlines. Wildfire response agencies act on what we ship. You will work alongside remote sensing scientists who define what the products must be, and own turning that into code that runs reliably, at scale, and on time.

This position is hybrid and requires working on-site in our San Jose, CA office three days per week.

Responsibilities

• Build, test, and maintain production data processing pipelines for infrared imagery, from raw frames through calibrated and orthorectified products.
• Improve pipeline performance against latency targets — profiling, parallelization, and eliminating fixed overhead in the critical path.
• Implement and operate workflow orchestration for continuous, automated processing across multiple satellites.
• Build monitoring, alerting, and operational tooling; participate in an on-call rotation for the systems you help build.
• Work with remote sensing scientists to turn algorithms and prototypes into production-ready, tested, maintainable code.
• Contribute to code review, testing practices, and technical documentation in a shared codebase.
• Diagnose and fix data quality and processing failures, including tracing problems back through the pipeline to their source.
• Learn new topics as needed (remote sensing measurement techniques, geospatial data engineering, customer domain-specific implications).

Qualifications

• BS, Masters, or PhD in Computer Science, Engineering, a physical science, or equivalent practical experience.
• BS +5 years or MS +3 years of relevant professional experience beyond internships.
• Solid Python skills, and experience writing code that other people depend on — tested, reviewed, and maintained over time.
• Familiarity with cloud infrastructure (AWS preferred) and containerized deployment.
• Comfort working with data at a scale where naive approaches stop working.
• Ability to work with a distributed, interdisciplinary team (scientists, engineers, data support).
• Willingness to learn the science domain well enough to reason about whether output is correct, not just whether the job succeeded.

Preferred Qualifications

• Experience with geospatial data tooling and formats (e.g. XArray, COG, GeoTIFF, NetCDF, GDAL, Zarr).
• Experience with workflow orchestration systems (Flyte, Airflow, or similar).
• Experience with performance profiling and optimization of data-intensive systems.
• Experience with satellite, remote sensing, or other scientific imagery pipelines.
• Infrastructure-as-code experience (Terraform or similar).
• Experience operating production systems on call.

Salary

The salary range for this role is $156,000 - $186,000, plus a competitive equity grant and comprehensive benefits package. Final compensation will be determined based on skills, qualifications, experience, and geographic location as assessed during the interview process.