Staff Reliability Engineer (System-Level Modeling — SOFC Systems)

Location: Bangalore, Karnataka

Time Type: Full time

Job Description

We are seeking a Staff Reliability Engineer to lead system-level reliability and availability modeling for Bloom Energy’s solid oxide fuel cell (SOFC) distributed power generation systems. This role focuses on building reliability block diagram (RBD) models, Markov/state-transition models, and Monte Carlo simulations to translate field and test data into actionable insights that improve uptime, service strategy, and product design decisions.

Key Responsibilities

Own and maintain system-level reliability/availability models for SOFC products, subsystems, and service architectures (redundancy, bypass, standby system, maintenance strategies, operating profiles).

• Develop and validate RBD models using ReliaSoft BlockSim; establish modeling standards, libraries, and peer-review practices.

• Build Markov/state-transition models and run Monte Carlo simulations to quantify availability, MTBF/MTTR, and uncertainty/sensitivity.

• Lead data-to-model parameterization from field, test, and supplier inputs (failure/repair distributions, censoring, restoration factors, common-cause assumptions) and calibrate to fleet performance.

• Deliver trade studies and recommendations to influence design and service decisions; communicate results clearly to crossfunctional stakeholders.

• Mentor engineers/analysts on reliability modeling methods and support global execution across India and the U.S.

Required Qualifications

• Bachelor’s or Master’s degree in Reliability, Mechanical, Electrical, Systems, Industrial Engineering (or related).

• 4-6 years of experience in reliability engineering, including ownership of system-level reliability/availability modeling for complex, repairable systems.

• Proficiency in RBD and availability modeling, including hands-on expertise with ReliaSoft BlockSim.

• Strong experience with Markov/state-transition modeling and Monte Carlo analysis. Strong statistical foundation for reliability data interpretation (failure/repair distributions, censored data, uncertainty communication).

• Strong interpersonal and communication skills to collaborate with product engineering, service, operations, and reliability stakeholders across time zones.

Preferred Skills

• Experience with fuel cells, power generation, or high-temperature electro-thermal systems.

• Experience using FRACAS/warranty/field data to calibrate models and validate projections against fleet performance. Reliability data analysis experience (e.g., Weibull, Crow-AMSAA) and ability to automate analysis using Python/MATLAB (version control preferred).

Why You’ll Love This Role

• High impact: your models directly influence design choices, service strategy, and customer uptime for future and deployed fleets.

End-to-end ownership: build the system view by connecting architecture, field performance, and maintainability into decision ready insights.

• Deep technical scope: apply RBD/BlockSim, Markov/state-transition modeling, and Monte Carlo simulation to complex, repairable systems.