Senior Remote Sensing Data Scientist, Cal/Val

Muon Space is building a family of infrared imaging missions designed for global wildfire detection and monitoring, weather and cloud characterization, and space-based environmental monitoring. Muon's IR Data Products team builds the analytics system that processes the data from our spacecraft's custom multispectral imaging instruments into data products and analytics for diverse end-user stakeholders from these missions. We are seeking a Data Scientist to join the team to build out the on-orbit data calibration system.

In this role, the candidate will join Muon's calibration team to build the production software systems that deliver calibration and image processing of the unique multi-spectral infrared data from several instrument variations in Muon's IR missions. This is a data science role with a strong software engineering focus: the successful candidate will translate calibration algorithms into hardened production pipelines, complete with monitoring and alerting, unit and integration testing, and automated diagnostic visualizations that keep calibration and image quality observable end-to-end. As the FireSat constellation scales, this role will take on an expanded mandate that spans both the FireSat Initial Operating Capability (IOC) commissioning and Muon's Space-Based Environmental Monitoring (SBEM) program. In the near term, the candidate will build out and operate the calibration software stack for the three FireSat satellites of the IOC constellation and stand up the automated testing and monitoring tooling that keeps that stack healthy at constellation scale. In parallel, the candidate will develop the production calibration infrastructure for Muon's SBEM instruments — a next-generation sensor suite featuring additional infrared spectral bands and significantly more stringent radiometric calibration requirements than the FireSat camera. As the SBEM program advances toward its 2027 launch, the candidate will first collaborate with the IR Instrument team on pre-launch calibration software and test harnesses, then lead the deployment and on-orbit operation of the SBEM calibration pipelines.

This position is hybrid and requires working on-site in our Denver, CO office three days per week.

• Design, build, and operate production-grade calibration and image-processing pipelines for the multispectral infrared imagery from Muon's FireSat and SBEM missions.
• Translate calibration algorithms — such as dark/offset correction, non-uniformity correction (NUC), radiometric gain and linearity, bad-pixel identification and replacement, and band-to-band registration — from research prototypes into hardened, well-tested production code, and own the testing strategy across unit, integration, and regression suites over representative lab and on-orbit datasets.
• Analyze pre-launch (thermal-vacuum, integrating sphere) and on-orbit calibration data to derive, validate, and trend calibration coefficients, and build monitoring, alerting, and automated diagnostic visualizations that surface calibration accuracy, noise, uniformity, and image-quality metrics as data flows through the pipelines.
• Contribute to CI/CD, deployment, containerization, and observability tooling that keeps calibration services reliable in production, and partner with calibration scientists and the IR Instrument team to plan and execute pre-launch and on-orbit calibration campaigns for the SBEM instruments and productionize their algorithms.
• Drive engineering best practices across the calibration codebase — code review, version control, documentation, versioned management of calibration coefficients and lookup tables, and continuous improvement of test coverage and reliability.
• Work cross-functionally with calibration scientists, IR instrument engineers, and product teams to build and maintain operational calibration services and ensure the scientific quality, quantitative validation, and radiometric integrity of Muon's IR data products — including uncertainty budgets and cross-calibration against on-board calibrators, blackbody references, and vicarious calibration sites
• Learn new topics as needed (measurement techniques, geospatial data engineering, software engineering, customer domain-specific implications)

• PhD with 3+ years, MS with 6+ years, or BS with 8+ years of industry experience
• 4+ years of experience calibrating imaging instruments
• Hands-on experience with complex data from new imaging instruments
• Proven track record shipping and operating production data or analytics pipelines for scientific data — including monitoring, logging, alerting, and automated testing — ideally in a remote sensing, calibration, or other measurement-instrument context
• Demonstrated experience taking scientific or numerical algorithms — for example calibration, image-processing, or signal-processing algorithms — from prototype to hardened, maintainable production code, including designing unit and integration test suites and quantitative validation against reference data
• Exceptional Python software engineering skills, including modern packaging, testing frameworks (e.g., pytest), version control, code review, and CI/CD workflows
• Solid grounding in statistics, applied mathematics, and enough instrument physics to reason about calibration algorithms, radiometric error budgets, and their diagnostics — and to design meaningful automated quality visualizations on top of them
• Ability to work with a distributed, interdisciplinary team (scientists, engineers, data support)
• Ability to thrive in a fast-paced start up environment

• Experience with mid-wave infrared instruments and MWIR data processing, and hands-on experience calibrating on-orbit imaging instruments — radiometric, spectral, and geometric
• Deep knowledge of the science of remote sensing and radiometric calibration, including SI-traceability and uncertainty analysis.
• Experience with detector characterization (dark current, non-uniformity, linearity, noise, MTF, or PRNU/DSNU), calibration campaign design (blackbodies, integrating spheres, on-board calibrators, deep convective clouds, lunar or vicarious calibration sites), and/or geospatial data processing
• Familiarity with common geospatial data tooling and formats (e.g. XArray, COG, NetCDF), and with building automated visualization or dashboarding tools for scientific data (e.g., Plotly, Panel, Streamlit, Grafana)
• Familiarity with containerization and workflow orchestration (Docker, Kubernetes, Airflow, Prefect, Argo, or similar)
• Experience with cloud-native systems and infrastructure-as-code (AWS preferred)
• Experience working with large TB-sized datasets, and domain expertise in geospatial analytics

The salary range for this role is $192,000 - $213,000.00, 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.