Muon Space designs, manufactures, and operates Halo satellite constellations and ground segments, integrating propulsion, RF/IR and passive microwave sensors, turnkey payload-to-operations services from its high-capacity San Jose production facility.
<h2><strong>About the role</strong></h2> <p>Muon seeks a Systems Engineer, Mission Success & Performance to join our Mission Engineering team. As we scale the Muon Mission Foundry, we need a strategic architect of mission success, someone who champions predictable mission outcomes across the entire Mission Execution process, ensuring our operational and business objectives are achieved consistently and reliably. The ideal candidate has deployed revenue-generating systems in the field, understanding the nuances and practicalities of transitioning from technology demonstrations to scalable operational capacity.</p> <p>This is not a traditional, compliance-heavy Mission Assurance role. This is a highly cross-functional role that spans the full lifecycle of mission design and execution, guaranteeing the technical integrity of our process as we “build the machine that builds the machines”. During the pre-launch activities, you will act as the vanguard for mission readiness, working with Mission Lead System Engineers (MLSEs) to drive right-sized Verification & Validation (V&V) campaigns that balance rigor and risk-tolerance with speed of Assembly, Integration, and Test (AI&T). Post-launch, you will work with operators to maximize the operational reality and business value of the assets, analyzing performance to close the loop between space and the future platform designs. Bridging both of these phases is a heavy focus on our autonomy and resilience capabilities, working on roadmap capabilities where you will shape fault management to drastically reduce operator toil.</p> <p>Parallel to all these efforts, you will act as a key technical stakeholder for the internal tooling roadmaps that enable this scaling. At Muon, "right-sizing" goes beyond technical risk; you will ruthlessly prioritize engineering efforts, balancing the need to fix painful internal processes against the drive to improve gross margins and overarching business outcomes.</p> <h2><strong>Responsibilities</strong></h2> <ul> <li>Enable the Muon Mission Foundry by driving processes and architectural decisions that allow Muon to scale spacecraft production and mission operations reliably and repeatably, moving beyond legacy quality assurance paradigms.</li> <li>Partner with Mission Systems Engineers to own and track V&V compliance, verification progress, and test coverage campaigns.</li> <li>Streamline AI&T workflows by identifying V&V bottlenecks and championing pragmatic Test Like You Fly (TLYF) standards.</li> <li>Analyze on-orbit telemetry and platform operations to squeeze maximum utility and capacity out of deployed assets</li> <li>Drive predictable outcomes by ensuring on-orbit performance closely matches pre-flight models, monitoring trends and impacts to mission SLAs, and understanding and proving the accuracy of the specifications we sell to customers.</li> <li>Own the fleet-learning loop for cross-cutting technical issues that affect multiple missions or the platform baseline: deciding what warrants dedicated engineering focus, chartering multidisciplinary teams to drive root cause and prevention, and closing the loop back into design so lessons compound across the constellation</li> <li>Collaborate with key stakeholders to align requirements, resolve interface ambiguities, and keep delivery synchronized on cross functional autonomy and resilience efforts</li> <li>Act as a key technical stakeholder supporting product roadmaps for internal tooling (e.g., MuSim, power analysis, data throughput), and utilizing your own software skills to build upon and extend baseline code, ensuring the tools enable the scaling of the Foundry.</li> <li>Business-Driven "Right-Sizing": Make pragmatic decisions that balance engineering pain points against direct business outcomes, prioritizing work that moves the needle on revenue over simply policing internal processes.</li> </ul> <h2><strong>Qualifications<em> </em></strong></h2> <ul> <li>M.S. or higher degree in an engineering field plus 8+ years of experience working in a multi-disciplinary environment, ideally with exposure to mission design, spacecraft operations, and systems architecture</li> <li>Experience with deployed systems in the field, operating in high reliability, performance critical environments</li> <li>Proven business acumen within an engineering context, understanding how asset capacity, uptime, and system resilience directly impact gross margins and revenue generation.</li> <li>Extensive experience in AI&T workflows and V&V strategies, specifically tracking defect escape rates, and test coverage</li> <li>Strong software skills (e.g., Python, Julia) with the ability to build upon existing codebases, coupled with a collaborative approach to supporting internal tooling roadmaps.</li> <li>Demonstrated ability to model system performance (power, thermal, data throughput) and validate those models against real-world, on-orbit data.</li> <li>Excellent communication and prioritization skills, with the ability to confidently balance technical risk with agile business constraints.</li> <li>Ability to rapidly change roles/responsibilities while working in a high-paced, rewarding work environment</li> </ul> <h2><strong>Nice-to-have Skills</strong></h2> <ul> <li>Deep understanding of spacecraft autonomy and fault management architectures, including FMECA, tiered response design, and the operational integration of FSW and GSW, with the ability to translate a fault management philosophy into concrete monitor definitions, safe mode designs, and recovery sequences</li> <li>Able to write requirements that software teams can implement and review FSW designs and code base for autonomy behavior.</li> <li>Experience as a lead systems engineer or technical stakeholder in an agile environment</li> <li>Remote sensing instrument experience across multiple modalities (e.g. optical, multispectral, RF), and their associated data pipelines</li> <li>Hands-on expe