Technical Specialist, Battery Algorithms and Digital Twin, Ford Energy

Posted 2 Hours Ago
Be an Early Applicant
Dearborn, MI, USA
Hybrid
116K-218K Annually
Senior level
Automotive • Software • Energy • Utilities • Manufacturing • Renewable Energy
A wholly owned subsidiary of Ford Motor Company dedicated to accelerating US energy independence. www.fordenergy.com
The Role
Own the battery intelligence stack for grid-scale and commercial BESS products. Lead production-grade SOC, SOH, thermal, power capability, degradation, RUL, diagnostics, and digital twin algorithms across cell, pack, and container levels. Define edge-cloud architecture, validation, field-data feedback, and deployment strategies while collaborating across BMS, EMS, controls, modeling, and software teams. Translate battery physics into deployable algorithms, mentor engineers, and align technical decisions with safety, warranty, performance, and dispatch requirements.
Summary Generated by Built In
Ford Energy is a newly formed, wholly-owned subsidiary of Ford Motor Company dedicated to accelerating U.S. energy independence. Leveraging Ford's century of manufacturing excellence and world-class battery energy storage systems (BESS) technology, Ford Energy designs, manufactures, and services grid-scale and commercial DC battery energy storage systems (BESS). Ford Energy is uniquely positioned to capture the growing demand for reliable, US-built energy storage systems. We are not just building batteries; we are building the infrastructure for the next generation of the American grid.
Why Ford Energy?
At Ford Energy, you have the backing of an industrial manufacturing powerhouse with the agility of a dedicated energy startup offering industry leading technology. We offer a competitive compensation package including performance-based bonuses, Ford vehicle discounts, and the opportunity to shape the energy strategy of one of the world's most iconic brands. Learn more at https://fordenergy.com.
In this position...
Ford Energy is seeking a Technical Specialist to own the battery intelligence stack for our BESS products: the state estimation, diagnostics, prognostics, and digital twin capabilities that determine how safely, reliably, and profitably a storage system performs over a life of 20+ years.
This role is for someone who has already shipped battery algorithms and wants to do it again at the start of a new product line. You will set the technical direction and stay hands-on, building, validating, and deploying algorithms that run on production BMS hardware and in the cloud, from cell to pack to container. Because Ford Energy is new, your decisions on architecture, data, and validation will become the foundation of the platform, not a patch on an existing one. You will work most closely with the BESS Cell, Modeling, BMS, EMS, and Digital Services teams, and draw on Ford's Auto battery organization for proven methods and test data, adapting them to stationary storage, where duty cycle, chemistry, and business case differ.
What you will own...
  • Production-grade state estimation: SOC, SOH, Dynamic OCV, and power/energy capability estimators that meet defined accuracy, robustness, and compute targets across temperature, aging, and partial-cycle duty.
  • A deployable digital twin architecture: a defined edge (BMS/EMS) and cloud split, with data, model, and interface specifications agreed with BMS, EMS, and Digital Services.
  • A field-data feedback loop: a working pipeline from operating systems to model recalibration, with drift monitoring and a release process for algorithm updates.
  • Prognostics the business can use: degradation and Remaining Useful Life (RUL) models with quantified uncertainty that support warranty, performance guarantees, and dispatch decisions.
  • Early-warning diagnostics: fault and anomaly detection that contributes to the safety case, with false-alarm and missed-detection targets set and measured.
  • A validation framework: test-to-field correlation, SIL/HIL coverage, and release criteria the whole organization trusts.

What you'll do...
  • Lead battery intelligence development across the BESS architecture, and 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, and set the 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, working with Battery Modeling to turn electrochemical, thermal, and degradation models into reduced-order forms suited to embedded execution.
  • Design, develop, and deploy algorithms for:
    • SOC, including approaches that work with flat-OCV chemistries such as LFP
    • SOH, capacity and resistance tracking, and state of power
    • Thermal state estimation
    • RUL and degradation prediction, covering calendar and cycle aging
    • Cell imbalance, anomaly, and fault detection, including early indicators of safety events
    • Link lab testing, validation, and field monitoring into one workflow, and quantify uncertainty with explicit error and confidence targets.
    • Lead technical reviews, architecture decisions, and deployment strategy; align modeling, hardware, controls, and software organizations around them.
    • Adapt algorithms, monitoring approaches, and validation methods from Ford's Auto battery teams to BESS needs, and share what you learn back.
    • Mentor engineers across modeling, controls, and software, and help shape the battery intelligence team as it grows.

You'll have...
  • 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 (vehicle, stationary storage, or consumer device), meaning code or models that ran on real hardware or in a live fleet, not only in simulation. Includes 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, and familiarity with reduced-order electrochemical or semi-empirical aging models.
  • Solid understanding of Li-ion physics: electrochemistry, thermal behavior, and aging mechanisms (e.g., SEI growth, lithium plating, loss of active material).
  • Proficiency in Python and MATLAB/Simulink, with 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, and the ability to present trade-offs clearly to executives and non-specialists.

Even better, you may have...
  • PhD in a battery-relevant discipline, or a publication/patent record in state estimation, aging, or controls.
  • Algorithms running in a deployed fleet: over-the-air updates, model-drift monitoring, and learning from field returns and warranty data.
  • Stationary storage and LFP experience, including SOC/SOH estimation on flat OCV curves and long calendar-life behavior.
  • Model-based design, auto-code generation, and SIL/HIL validation of BMS software.
  • Machine learning for SOH/RUL or anomaly detection, with judgment on when physics-based, data-driven, or hybrid methods fit best.
  • Digital twin or time-series data platforms (cloud, streaming, MLOps) and edge-to-cloud architecture.
  • Knowledge of BESS safety standards and practices (e.g., UL 9540/9540A, IEC 62619, NFPA 855) and thermal-runaway early detection.
  • Experience linking degradation models to warranty, levelized cost of storage, or dispatch optimization, and familiarity with PCS/EMS interactions and grid-service duty cycles.
  • Prior experience in an OEM battery organization, or standing up an algorithm team or platform from scratch.
  • Location & Travel
    • Location: Dearborn, MI / Hybrid
    • Reports to: Manager BESS Platform

You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!
As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder...or all of the above? No matter what you choose, we offer a work life that works for you, including:• 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 and more• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more• 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 • A generous schedule of paid holidays, including the week between Christmas and New Year's Day • Paid time off and the option to purchase additional vacation time.
This position is leadership level 6 and ranges from $115,500-$218,100.
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
For more information on salary and benefits, click here: https://fordcareers.co/LL6
Company: As Ford establishes a wholly owned subsidiary focused on Battery Energy Storage Systems, this role will initially be employed by Ford and is expected to transition to the subsidiary within one year.
Visa sponsorship is not available for this position.
Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.
We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, if you need a reasonable accommodation for the online application process due to a disability, please call 1-888-336-0660.
This position is hybrid with a requirement to be onsite four or more days per week.
#LI-Hybrid
#li-RC1
#FordEnergy

Skills Required

  • 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 or live fleets.
  • 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 lithium-ion electrochemistry, thermal behavior, and aging mechanisms.
  • Proficiency in Python and MATLAB/Simulink.
  • Working familiarity with C, C++, or another production programming language.
  • Experience calibrating and validating models against cycling, characterization, and ideally field data, including estimation-error quantification.
  • Technical leadership across functions without formal authority and ability to present trade-offs to executives and non-specialists.
  • 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 or warranty data.
  • Stationary storage and LFP experience, including SOC/SOH estimation on flat OCV curves and long calendar-life behavior.
  • Model-based design, auto-code generation, and SIL/HIL validation of BMS software.
  • Machine learning experience for SOH/RUL or anomaly detection.
  • Experience with digital twins, time-series data platforms, cloud, streaming, MLOps, or edge-to-cloud architecture.
  • Knowledge of BESS safety standards including UL 9540/9540A, IEC 62619, or NFPA 855.
  • Experience linking degradation models to warranty, levelized cost of storage, or dispatch optimization, and 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.

Ford Energy Compensation & Benefits Highlights

  • Healthcare Strength — Feedback suggests immediate medical, dental, vision, prescription-drug, mental-health, and wellness coverage are available and positioned as a core strength.
  • Retirement Support — Retirement savings plans with company contributions or matching are highlighted, along with financial-planning resources that enhance total rewards.
  • Parental & Family Support — Paid parental leave, family-care days, backup childcare, and family-building benefits such as fertility, adoption, and surrogacy assistance are emphasized.

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The Company
55 Employees
Year Founded: 2026

What We Do

Ford Energy is uniquely positioned to capture the growing demand for reliable, US-built energy storage systems. Leveraging Ford’s century of manufacturing excellence and world-class battery energy storage systems (BESS) technology, Ford Energy designs, manufactures, and services grid-scale and commercial DC battery energy storage systems. We are not just building batteries; we are building the infrastructure for the next generation of the American grid. www.fordenergy.com

Ford Energy Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site:
United States

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