Technical Specialist, Battery Algorithms, Digital Twin

Ford Motor Company

. Lead battery intelligence development across the BESS architecture .

Posted 10/9/2026full-timeDearborn • Michigan • United StatesSeniorLead💰 $115,500 - $218,100 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in battery intelligence development, including algorithm design for SOC, SOH, and thermal estimation, while effectively leading cross-functional teams and mentoring engineers. Proficient in Python, MATLAB/Simulink, and model-based design, with a strong understanding of Li-ion electrochemistry and BESS safety standards.

Highest-signal resume keywords

Battery Algorithm DevelopmentPython ProficiencyModel-Based DesignTechnical LeadershipLi-Ion Electrochemistry Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Battery Algorithm DevelopmentModel Calibration and ValidationDigital Twin DevelopmentElectrochemical ModelingFault Detection AlgorithmsMachine Learning for Anomaly DetectionKalman-Family ObserversReduced-Order ModelingThermal EstimationState Estimation

Soft Skills

Technical LeadershipClear CommunicationMentoring

Tools & Technologies

PythonMATLAB/SimulinkC/C++Cloud PlatformsMLOpsStreaming Data PlatformsSIL/HIL Validation

Industry Keywords

Battery Energy Storage Systems (BESS)Li-Ion Safety StandardsUL 9540/9540AIEC 62619NFPA 855Deployed-Fleet AlgorithmsOver-the-Air UpdatesGrid-Service Duty CyclesOEM Battery Organization ExperienceAging Mechanisms

Tech Stack

Tools & technologies

CloudPythonC++

About the role

Key responsibilities & impact

Lead battery intelligence development across the BESS architecture
Engage Pack, Container, PCS, DC Block, AC, and Controls teams as program needs require
Define requirements for monitoring, diagnostics, prognostics, and digital twins, including accuracy, latency, compute, memory, data-rate, and sensor needs
Set interfaces between the algorithm stack and BMS, EMS, and cloud platforms
Translate battery physics, degradation mechanisms, and operational requirements into implementable software and control strategies
Build hybrid physics-based and data-driven digital twins at cell, pack, and container levels
Develop reduced-order electrochemical, thermal, and degradation models suited to embedded execution
Design, develop, and deploy SOC, SOH, state-of-power, thermal estimation, RUL, degradation prediction, imbalance, anomaly, and fault-detection algorithms
Link lab testing, validation, and field monitoring into one workflow
Quantify uncertainty with explicit error and confidence targets
Lead technical reviews, architecture decisions, and deployment strategy
Align modeling, hardware, controls, and software organizations
Adapt algorithms and validation methods from Ford Auto battery teams to BESS needs
Mentor engineers and help shape the battery intelligence team

Requirements

What you’ll need

Master's degree with 8+ years of experience, or PhD with 5+ years, in Electrical, Mechanical, Chemical, or Controls Engineering, Materials Science, or a related field
Hands-on experience developing and deploying battery algorithms on production systems; experience with at least two of SOC, SOH, state of power, RUL/degradation, thermal estimation, or fault detection
Working knowledge of equivalent-circuit models and Kalman-family observers
Familiarity with reduced-order electrochemical or semi-empirical aging models
Solid understanding of Li-ion electrochemistry, thermal behavior, and aging mechanisms, including SEI growth, lithium plating, and loss of active material
Proficiency in Python and MATLAB/Simulink
Working familiarity in C/C++ or another production language
Experience calibrating and validating models against cycling, characterization, and ideally field data, including quantifying estimation error
Technical leadership across functions without formal authority
Ability to present trade-offs clearly to executives and non-specialists
Visa sponsorship is not available
Must be legally authorized to work in the United States
PhD in a battery-relevant discipline or publication/patent record in state estimation, aging, or controls
Experience with deployed-fleet algorithms, over-the-air updates, model-drift monitoring, and field/warranty data
Stationary storage and LFP experience
Model-based design, auto-code generation, and SIL/HIL validation of BMS software
Machine learning for SOH/RUL or anomaly detection
Digital twin or time-series data platforms, cloud, streaming, MLOps, and edge-to-cloud architecture
Knowledge of BESS safety standards such as UL 9540/9540A, IEC 62619, and NFPA 855
Experience linking degradation models to warranty, levelized cost of storage, or dispatch optimization
Familiarity with PCS/EMS interactions and grid-service duty cycles
Prior experience in an OEM battery organization or establishing an algorithm team or platform from scratch

Benefits

Comp & perks

Performance-based bonuses
Ford vehicle discounts
Immediate medical, dental, vision and prescription drug coverage
Flexible family care days
Paid parental leave
New parent ramp-up programs
Subsidized back-up child care
Adoption and surrogacy expense reimbursement
Fertility treatments
Vehicle discount program for employees and family members and management leases
Tuition assistance
Established and active employee resource groups
Paid time off for individual and team community service
Paid holidays, including the week between Christmas and New Year’s Day
Paid time off
Option to purchase additional vacation time