Senior Cell Validation & Reliability Engineer

Peak Energy•Burlingame, CA

13d•Onsite

About The Position

Peak Energy Technologies is seeking a Senior Cell Validation & Reliability Engineer with two primary charters. First, validate the electrical and mechanical integration of supplier cells into Peak Energy's energy storage systems — moving beyond verification of the cell specification to quantifying how population variance (cell-to-cell and batch-to-batch) impacts system-level performance. Second, own cell reliability: the test plans that generate data, the statistical analysis of that data, and the final cell-level input to system reliability evaluation. This engineer designs the studies, owns the analysis, and delivers validation verdicts and reliability inputs. Test execution is carried by the cell test engineering team, predictive modeling by the cell modeling function, and system design and system-level reliability evaluation remain with ESS engineering. Peak Energy is seeking a Senior Cell Validation & Reliability Engineer to own the validation and reliability foundation for the cells integrated into our energy storage systems. This role will move beyond cell specification verification to quantify how cell-to-cell and batch-to-batch variation impacts system-level performance and reliability. You will design the studies, own the statistical analysis, and deliver cell-level validation verdicts and reliability inputs that inform Peak Energy's system design and 20-year calendar life expectations. You will work closely with cell test engineering, cell modeling, ESS engineering, supplier quality, and other cross-functional teams to translate cell performance and variation into actionable system requirements. Test execution will be carried out by the cell test engineering team, predictive modeling by the cell modeling function, and system design and system-level reliability evaluation by ESS engineering. This role owns the cell-side validation and reliability inputs that connect those functions. The ideal candidate combines strong battery validation experience with applied reliability statistics and is comfortable turning complex test data into clear engineering decisions.

Requirements

B.S. in Mechanical, Electrical, or Chemical Engineering or a related field; M.S. preferred.
5+ years in battery cell/module/pack validation or reliability engineering within automotive or stationary energy storage.
Reliability statistics: Weibull / life-data analysis, accelerated life testing, and confidence-bound methods for life claims.
Applied statistics in an engineering context: design of experiments, capability analysis, measurement system analysis, sample-size justification.
Hands-on familiarity with cell test methods: cyclers, environmental chambers, force/displacement measurement, and thermal instrumentation.
Depth in one integration axis — mechanical (compression, thermal interface) or electrical (BMS, system electrical performance) — with working competence in the other.
Working knowledge of BMS fundamentals: SOC/SOH estimation, cell balancing, and protection limits.
Proficiency in Python or equivalent for engineering data analysis.

Nice To Haves

Reliability methods: reliability block diagrams, failure-rate (FIT) allocation, MTBF modeling.
Experience owning DVP&Rs and driving validation programs from plan through sign-off.
Sodium-ion or LFP cell experience.
Experience partnering with modeling teams on equivalent-circuit, thermal, and degradation model validation.
DFMEA participation on module/pack programs.

Responsibilities

Validate the electrical and mechanical integration of supplier cells into Peak Energy ESS platforms; own the cell-side validation verdict at each integration point.
Move validation from spec verification to population statistics: design cell-to-cell and batch-to-batch variation studies and quantify how variance propagates to system-level performance — balancing burden, thermal gradients, mechanical preload windows, and energy/power delivery.
Mechanical: validate cell behavior under system-representative compression; characterize force versus state of charge and swell over life; deliver force–displacement–life datasets that inform foam/pad selection and preload design by systems engineering.
Electrical & BMS: Assist in analysis with measured variation accounted for of OCV characterization, equivalent-circuit parameters; quantify cell-in-system versus bench performance deltas.
Establish the statistical foundation: measurement system analysis (MSA / Gauge R&R) across cell test equipment, capability analysis against specification, and statistically justified sample sizes, acceptance criteria, and validation exit criteria.
Own the cell reliability test roadmap: inform sample size requirements for calendar life, cycle life, and accelerated aging test plans designed explicitly to inform reliability analysis — not only to characterize performance.
Deliver the authoritative cell-level input to system reliability evaluation: failure-rate estimates, life distributions under product duty cycles, degradation trajectories, and derating guidance.
Track reliability performance across supplier lots and chemistries; participate in root cause analysis of cell-related reliability failures and feed findings back into test plans and supplier requirements.
Own the cell-requirements and reliability-input handoffs; participate in DFMEAs for cell-driven failure modes.
Share variation and reliability findings with supplier quality: this role owns the performance and reliability implications of variation.
Pair with cell modeling: measured variation and life data validate equivalent-circuit, thermal, and degradation models; model predictions guide test-plan design.