Job description

About the role Muon Space is building and operating a growing portfolio of infrared (IR) space missions that generate mission-critical Earth observation data for a diverse and expanding set of customers. These missions include the FireSat constellation, which delivers calibrated IR imagery and derived wildfire products to wildfire operators, the scientific community, the US Government, and commercial partners; and the Space Based Environmental Monitoring (SBEM) mission, which provides data for weather and cloud characterization, situational awareness, and a broad range of additional use cases. Muon's IR Data Products team owns the multi-mission, multi-customer software systems that process, store, and disseminate the data from these missions — turning raw downlink into calibrated imagery and derived products, and delivering those products reliably and at low latency to customers at scale. This role is an architecture and technical-leadership seat for the Software focus area of the IR Data Products team. The engineer will own architecture and cross-team execution across defined IR data-system domains, translating longer-term technical direction into multi-quarter designs and delivered production systems. This role will lead multi-quarter initiatives to design and build scalable software architectures that make the system fast, cheap, reliable, evolvable, and ready for many-satellite scale. In this role, the candidate will work across four key areas: Architecture & implementation leadership for the next-year horizon: Own key aspects of the architectural direction for the data systems for Muon’s IR Missions — pre-processing, processing directives & routing, delivery orchestration, compliance evaluation, and the orchestration platform itself. Low-latency optimization & core infrastructure: Own key aspects of the technical roadmap to low-latency processing. Own structural designs such as event-driven microservices, cloud infrastructure design and optimization, and algorithmic optimizations. Geospatial tooling: Own key aspects of the architectural direction for how we store, catalog, serve, and version geospatial data (NetCDF, Zarr, HDF, STAC, tile stores) at scale. MLOps foundations: Build the production foundations for ML products — model packaging, experiment tracking, GPU-backed training and inference — that our derived-product work (hotspots, perimeters, fire behavior) will increasingly depend on. Additionally, the role will represent the team in cross-functional design reviews, drive prioritization syncs with Technical Program Managers and Business Development, and set software standards for the team’s codebase and development practices. This engineer will mentor senior and mid-level engineers across the team and raise the bar on how we reason about failure modes, immutability, idempotency, and reprocessing. The ideal candidate is a hands-on staff-level engineer with a track record of leading multi-quarter architectural initiatives on production data platforms at scale. They combine deep experience with distributed data systems and modern workflow orchestration with real geospatial and (ideally) MLOps depth, and they are as comfortable writing a design document and driving cross-team alignment as they are debugging a complex piece of algorithm code. This position is hybrid and requires working on-site in our Denver, CO office three days per week. Responsibilities Own key aspects of the architectural design for the multi-mission, multi-customer IR data systems in partnership with the Principal Software Engineer: ingest, pre-processing, orchestration, storage and catalog, delivery, and the platforms that run all of the above. Lead the design and implementation of critical capabilities for Muon's IR missions from problem framing and design document through rollout, adoption, and operational hand-off. Own key aspects of the technical roadmap to low-latency processing including: structural designs such as event-driven microservices, cloud infrastructure design and optimization, and algorithmic optimizations. Set direction for geospatial data storage, cataloging, and serving at scale — including tradeoffs across formats, tile stores, STAC catalogs, bucket and IAM topology, and reprocessing / versioning strategy. Design and build the MLOps foundations for derived IR products — model packaging and versioning, experiment tracking, GPU-backed training and inference, A/B evaluation harnesses, and reproducibility — so ML-driven products can move from research to production on a well-paved path. Set software standards for the team — codebase organization, release engineering, CI, testing, documentation, code review, observability, and operational excellence — and raise the bar on how the team reasons about failure modes, immutability, idempotency, and reprocessing. Provide technical leadership across functions: coordinate design and implementation with Product, Program Management, Business Development, and other Software teams; represent IR Data Products in cross-functional design reviews and design processes; and turn ambiguous requirements (latency budgets, compliance constraints, new missions, new customers) into concrete engineering plans. Qualifications Bachelor’s degree with 10+ years or MS with 8+ years or PhD with 5+ years of software engineering experience. Demonstrated success as a technical leader on production data platforms at scale — with the designs and rollouts to show for it. Demonstrated experience designing and operating production data pipelines on AWS with a modern workflow orchestrator (e.g., Flyte, Airflow, Prefect, Argo, or equivalent). Track record of leading multi-quarter architectural initiatives that spanned multiple services or teams. Experience with latency optimization: measurement discipline, benchmarking, per-stage instrumentation, right-sizing, fan-out, caching, async I/O, and knowing when the answer is structural rather than algorithmic. Strong operational mindset: observability, SLOs, on-call, safe deploys, hotfix protocols, immutability, and reproducibility. Excellent technical writing and cross-functional communication — comfortable driving alignment across engineers, scientists, PMs, and adjacent platform / flight-software teams. Preferred Qualifications Experience with event-driven / microservices architectures: queues, event routing, backpressure, idempotency, retries, DLQs, and clear service contracts. Familiarity with modern workflow platforms such as Union.ai / Flyte v2. Terraform / IaC ownership of AWS resources, and hands-on experience shaping IAM boundaries between environments. Prior work on geospatial / remote sensing systems at scale. Fluent with the tradeoffs behind geospatial storage formats, tile stores, and STAC. Hands-on MLOps experience: model packaging and versioning, experiment tracking (MLflow, W&B, or similar), GPU-backed training and inference, feature stores, A/B harnesses. Experience with GPU acceleration for image processing (e.g., JAX, CuPy, CUDA) or ML inference at scale. Experience in satellite ground-segment or a comparable domain where compliance, provenance, and data lineage are first-class concerns. Experience introducing latency SLOs and benchmarking discipline to a team. Prior experience serving imagery / tiled geospatial data to external customers or partner platforms. Salary The salary range for this role is $216,000 - $239,000 , 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. About Muon Space Founded in 2021, Muon Space is an end-to-end Space Systems Provider that designs, builds, and operates LEO satellite constellations delivering mission-critical data. Our revolutionary, integrated technology stack enables customers to optimize every dimension of their missions for faster time-to-orbit and superior constellation remote sensing performance. Our state-of-the-art facility in the heart of Silicon Valley is optimized for manufacturing spacecraft and rapid, flexible payload integration at scale. From climate monitoring to national security, Muon Space is dedicated to delivering Earth Intelligence for a safer and more resilient world. Taking Care of Our Team At Muon salary is only part of our total compensation package. In addition to salary, full-time employees receive equity compensation as well as benefits including medical, dental, and vision insurance, a 401k retirement plan, short & long term disability and life insurance. We also offer three weeks paid vacation for new employees, along with 12 paid holidays, unlimited sick time and paid parental leave. Our mission embraces the entire planet and we believe our team should too. Muon is dedicated to creating a diverse and dynamic company and workforce. We believe in equal employment opportunity regardless of race, color, ancestry, religion, sex, age, national origin, citizenship, sexual orientation, marital status, disability, or gender identity. We value diversity in the workplace, and that starts with our applicants. We encourage you to apply, even if you don't check all the boxes, and we look forward to reviewing your application! In addition, if you need a reasonable accommodation as part of your application for employment or interviews with us, please let us know. Muon is currently registered and able to hire in the following states: AL, AZ, CA, CO, CT, DC, FL, GA, IL, IA, ID, MD, MA, MI, MN, MO, NJ, NY, NC, OH, OR, PA, TN, TX, VT, VA, WA ITAR/EAR Requirements This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful, permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. The Company may, for legitimate business reasons, decline to pursue any export licensing process.

Requirements

Must-haves

In this role, the candidate will work across four key areas:
Geospatial tooling: Own key aspects of the architectural direction for how we store, catalog, serve, and version geospatial data (NetCDF, Zarr, HDF, STAC, tile stores) at scale.
This position is hybrid and requires working on-site in our Denver, CO office three days per week.
Lead the design and implementation of critical capabilities for Muon's IR missions from problem framing and design document through rollout, adoption, and operational hand-off.
Own key aspects of the technical roadmap to low-latency processing including: structural designs such as event-driven microservices, cloud infrastructure design and optimization, and algorithmic optimizations.
Set direction for geospatial data storage, cataloging, and serving at scale — including tradeoffs across formats, tile stores, STAC catalogs, bucket and IAM topology, and reprocessing / versioning strategy.
Bachelor’s degree with 10+ years or MS with 8+ years or PhD with 5+ years of software engineering experience.
Demonstrated success as a technical leader on production data platforms at scale — with the designs and rollouts to show for it.
Demonstrated experience designing and operating production data pipelines on AWS with a modern workflow orchestrator (e.g., Flyte, Airflow, Prefect, Argo, or equivalent).
Track record of leading multi-quarter architectural initiatives that spanned multiple services or teams.
Experience with latency optimization: measurement discipline, benchmarking, per-stage instrumentation, right-sizing, fan-out, caching, async I/O, and knowing when the answer is structural rather than algorithmic.
Strong operational mindset: observability, SLOs, on-call, safe deploys, hotfix protocols, immutability, and reproducibility.
Excellent technical writing and cross-functional communication — comfortable driving alignment across engineers, scientists, PMs, and adjacent platform / flight-software teams.

Nice-to-haves

Experience with event-driven / microservices architectures: queues, event routing, backpressure, idempotency, retries, DLQs, and clear service contracts.
Familiarity with modern workflow platforms such as Union.ai / Flyte v2.
Terraform / IaC ownership of AWS resources, and hands-on experience shaping IAM boundaries between environments.
Prior work on geospatial / remote sensing systems at scale.
Fluent with the tradeoffs behind geospatial storage formats, tile stores, and STAC.
Hands-on MLOps experience: model packaging and versioning, experiment tracking (MLflow, W&B, or similar), GPU-backed training and inference, feature stores, A/B harnesses.
Experience with GPU acceleration for image processing (e.g., JAX, CuPy, CUDA) or ML inference at scale.
Experience in satellite ground-segment or a comparable domain where compliance, provenance, and data lineage are first-class concerns.
Experience introducing latency SLOs and benchmarking discipline to a team.
Prior experience serving imagery / tiled geospatial data to external customers or partner platforms.

Application prep

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Benefits

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Dental

Vision

401k

Parental Leave