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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior-Staff Reliability Engineer - **Company:** Antares, LLC - **Location:** Torrance, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Systems Engineering, Unit Testing, Databases, Failure Mode Effects Analysis, R (Programming Language), Python (Programming Language), MATLAB, Minitab, Octave, Operational Databases, Reliability Engineering, SAS (Software), Technical Data Management Systems, Test Data, Mttr, Reliability of Systems, Programming Languages - **Published:** September 10, 2026 - **Apply:** https://startup.jobs/senior-staff-reliability-engineer-antares-9972071 ## About the Role * Bachelor's degree in engineering, applied mathematics, physics, statistics, or a related technical field. * Experience performing reliability, root cause analysis, failure analysis, statistical analysis, or similar quantitative engineering work on complex hardware systems. * Working knowledge of statistics, probability, failure modes, and reliability engineering fundamentals. * Ability to understand mechanical and electrical systems well enough to evaluate likely failure mechanisms and reliability risks. * Ability to analyze technical data, develop quantitative conclusions, and communicate recommendations to engineering teams. Preferred Skills and Experience: * Experience with reliability engineering in nuclear, aerospace, space, automotive, energy, defense, or other safety- or mission-critical hardware industries. * Experience with reliability block diagrams, fault trees, FMEA/FMECA, Weibull analysis, MTBF/MTTR, probabilistic risk assessment (PRA), availability modeling, or reliability growth methods. * Experience translating system-level availability or capacity factor targets into subsystem and component reliability requirements. * Experience with or understanding "risk informed component classification and knowledge with 10CFR50.69. * Familiarity with mechanical and electrical design, manufacturing processes, qualification testing, material capabilities/limitations, and common hardware failure mechanisms. * Experience using test, field, or production data to estimate failure rates and update reliability predictions. * Experience driving design changes or reliability improvement plans based on quantitative reliability analysis. * Familiarity with statistical tools or programming languages and relevant libraries used for engineering analysis, such as Python, MATLAB, Octave, R, Minitab, SAS, NCSS, or similar. ## Description * Own quantitative reliability analysis for the Antares R1 microreactor, including development and maintenance of reactor and plant level reliability, availability, and capacity factor models. * Establish reliability targets for reactor systems, subsystems, and critical components based on overall plant capacity factor, regulatory and mission requirements. * Translate top-level reactor availability and capacity factor goals into measurable reliability requirements for individual mechanical, electrical, controls, thermal, and balance-of-plant systems. * Develop and maintain reliability block diagrams, fault trees, failure mode analyses, and other quantitative models used to understand how component and subsystem failures affect overall reactor performance and availability. * Calculate and track key reliability metrics including failure rates, MTBF, MTTR, availability, probability of mission success, component life, and expected contribution to reactor downtime. * Identify the components and failure modes that have the greatest impact on reactor capacity factor and lead focused improvement efforts to reduce those risks. * Work directly with mechanical, electrical, controls, manufacturing, test, and reactor systems engineers to develop reliability improvement plans for the lowest-performing or highest-risk portions of the design. * Evaluate design alternatives and architecture trades based on their impact to reliability, redundancy, maintainability, serviceability, and reactor capacity factor. * Perform sensitivity and uncertainty analyses to determine which assumptions, failure rates, repair times, and component behaviors most strongly influence predicted reactor availability. * Develop reliability predictions using component test data, supplier data, industry databases, accelerated life testing, engineering analysis, and field experience. * Establish statistically sound methods for converting development and qualification test results into reliability estimates and confidence bounds. * Define reliability demonstration and qualification test strategies, including sample sizes, test durations, failure criteria, confidence levels, and statistical acceptance methods. * Use operational, manufacturing, inspection, and test data to continuously update reliability models and improve predictions as the reactor design matures. * Lead or support DFMEA, FMEA, FMECA, fault tree analysis, and related structured failure-mode investigations across reactor systems. * Partner with design teams early in the development process to identify single-point failures, wear-out mechanisms, common-cause vulnerabilities, inadequate redundancy, difficult-to-maintain components, and other reliability risks before designs are released. * Evaluate component degradation and life-limiting mechanisms including fatigue, creep, wear, corrosion, thermal cycling, radiation exposure, electrical degradation, and environmental effects as applicable to the reactor design. * Develop reliability growth plans for systems that do not initially meet program targets and track progress toward demonstrated reliability objectives. * Support decisions regarding redundancy, sparing, preventative maintenance, inspection intervals, replacement intervals, and repair strategies based on quantitative reliability and availability analysis. * Work with operations and deployment teams to understand expected maintenance and repair activities and accurately incorporate those activities into reactor availability and capacity factor predictions. * Establish clear reliability dashboards, metrics, and technical reviews that allow engineering leadership to understand the major drivers of reactor downtime and where engineering effort should be focused. * Communicate reliability risks and recommendations clearly to engineers and program leadership, including the quantitative impact of proposed design or operational changes on overall reactor performance. * Serve as a technical authority for reliability engineering methods and help establish Antares' internal standards, tools, processes, and best practices for designing highly reliable reactor systems. * Drive a culture in which reliability is treated as a design requirement and continuously improved through analysis, testing, manufacturing data, and operational learning rather than evaluated only after hardware is complete. ## 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