Principal Hardware Reliability Engineer

K2 Space•Los Angeles, CA

1d•$185,000 - $220,000

About The Position

As a technical authority on hardware reliability, you will own the development and execution of reliability strategies that enable our spacecraft to meet ambitious vehicle and constellation-level targets for probability of success and availability. You will define reliability requirements, build and apply advanced semi-empirical modeling techniques, and drive testing programs that identify and mitigate risks early in development. This role sits at the intersection of design, test, systems, and manufacturing, where you will integrate reliability models with program risk management and flow down clear, actionable requirements across subsystems. You will lead root cause investigations on critical hardware issues, mentor engineers across the reliability function, and play a key role in shaping K2’s reliability strategy as we scale toward high-volume satellite production. The ideal candidate is a technically strong, hands-on engineer who thrives in a fast-paced startup environment and is excited to build the reliability foundation for a new generation of large, capable spacecraft.

Requirements

B.S. degree in mechanical engineering, aerospace engineering, electrical engineering, materials science, or other related discipline
8+ years of experience in reliability engineering, hardware testing, failure analysis, or related fields in the space, automotive, semiconductor, or other high-reliability industries

Nice To Haves

M.S. or PhD in mechanical engineering, electrical engineering, chemical engineering, materials science, or other related discipline
Experience developing and executing life testing methods, including accelerated life testing (ALT) and reliability growth programs
Experience with accelerated failure time (AFT) modeling, including Norris-Landzberg and Arrhenius acceleration models, for translating ground test severity to flight conditions
Experience reconciling multiple ground test sources (QTP, ATP, HALT, HASS) and flight telemetry onto a single reliability model, including distinguishing workmanship/infant-mortality failure modes from wear-out mechanisms
Familiarity with success-run and zero-failure demonstration statistics, and sample-size/DOE methods for reliability test planning
Exposure to degradation-based reliability modeling (Gamma or Wiener process models, accelerated degradation testing) as a complement to binary pass/fail Weibull analysis
Experience with thermal, vibration, and TVAC qualification and acceptance testing approaches
Experience with EEE components (Electrical, Electronic, and Electromechanical), including semiconductor devices and packaging technologies, in high-reliability or space applications
Experience building reliability prediction models (Weibull, Kaplan-Meier, Monte Carlo, reliability block diagrams) and performing system-level analyses (FTA, PRA)
Strong foundation in statistical modeling and data analysis, with experience developing custom models for engineering or production data. Experience with Bayesian hierarchical modeling and MCMC tools (e.g., PyMC, Stan, NumPyro) for reliability parameter estimation is a plus
Proficiency in programming languages (such as Python or C++) for data analysis, statistical modeling, and reliability calculations
Familiarity with derating practices, Design for Excellence (DFX), and requirements flow-down in complex hardware systems
Experience with Physics of Failure (PoF) methodologies, including Sherlock or similar modeling tools, and identification of dominant failure mechanisms in electronic hardware and EEE components
Experience with reliability growth tracking or working toward probability of success / availability targets on vehicles or constellations
Strong cross-functional communication skills and ability to clearly present technical findings to both engineering and leadership teams
Experience in a fast-paced startup or new-space environment with high ownership and broad scope
Familiarity with FRACAS and test-effectiveness tracking processes

Responsibilities

Own the development and maintenance of top-level reliability requirements, models, and allocations across the full spacecraft and constellation portfolio to meet vehicle and constellation-level targets for probability of success and availability
Define and drive HALT/HASS strategies, accelerated testing plans, and reliability growth programs across spacecraft development and production, including test standardization, lot acceptance derivations, and success-run demonstration analysis to confirm campaigns meet flight-life requirements
Establish and evolve reliability modelling frameworks, including Weibull and Kaplan-Meier analysis, accelerated failure time (AFT) modeling (e.g., Norris-Landzberg, Arrhenius), Monte Carlo simulations, and Probabilistic Risk Assessment (PRA), reconciling QTP, ATP, HALT, HASS, and flight telemetry data onto a single wear-out model
Integrate reliability analyses with program risk management and drive actionable insights that influence design, manufacturing, and test decisions
Flow down reliability requirements to subsystems, including margins, screening levels, derating guidelines, and test requirements, and ensure consistent application across programs
Lead root cause investigations on critical hardware failures and drive systemic corrective actions that improve product robustness and mission reliability
Collaborate closely with design, systems, test, and manufacturing teams to embed reliability principles early in the development process and optimize for mass production
Mentor and develop junior and mid-level engineers on reliability methods, analysis techniques, and best practices, while helping shape the long-term technical direction and growth of the reliability function at K2 Space
Serve as a technical authority on reliability across multiple spacecraft programs, advising leadership on risk trade-offs and reliability strategy
Own FRACAS and test-effectiveness tracking to close the loop between failure data, corrective actions, and reliability predictions
Partner with responsible engineers to implement telemetry and instrumentation for degradation observability on flight and test hardware
Advance degradation-based and Bayesian reliability methods, including Gamma/Wiener process degradation models and MCMC-based hierarchical pooling, to extend the reliability framework beyond binary pass/fail testing