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Ford Motor Company

Builds vehicles for drivers and commercial fleets

Technical Specialist - Battery Algorithms and Digital Twin

Electrical EngineeringConfirmed live in the last 24 hours
Full-timeDearborn, MI, USA

About the Job

Requirements

  • A master's degree with at least 8 years of experience, or a PhD with at least 5 years of experience, in Electrical, Mechanical, Chemical, or Controls Engineering, Materials Science, or a related field.
  • Hands-on experience developing and deploying battery algorithms on production systems, including algorithms that ran on real hardware or in a live fleet rather than only in simulation; experience must include 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 lithium-ion physics, including electrochemistry, thermal behavior, and aging mechanisms such as SEI growth, lithium plating, and 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.
  • Ability to provide technical leadership across functions without formal authority and present trade-offs clearly to executives and non-specialists.

Responsibilities

  • Lead battery intelligence development across the BESS architecture, engaging 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 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 convert 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; and 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, aligning modeling, hardware, controls, and software organizations.
  • Adapt algorithms, monitoring approaches, and validation methods from Ford's automotive battery teams to BESS needs, and share lessons learned with those teams.
  • Mentor engineers across modeling, controls, and software, and help shape the battery intelligence team as it grows.

Desired Qualifications

  • A PhD in a battery-relevant discipline, or a publication or patent record in state estimation, aging, or controls.
  • Algorithms deployed in a fleet, including 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 are most suitable.
  • Digital twin or time-series data platforms, including cloud, streaming, MLOps, and edge-to-cloud architecture.
  • Knowledge of BESS safety standards and practices, including UL 9540/9540A, IEC 62619, and 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 establishing an algorithm team or platform from scratch.

About the Company

Ford Motor Company

Builds vehicles for drivers and commercial fleets

Ford Motor Company designs and builds vehicles for individual drivers and commercial fleets worldwide, spanning Ford trucks and SUVs and Lincoln luxury models. Its Mustang sports car and Bronco off-road vehicles sit alongside gasoline, hybrid and electric products. The company sells vehicles, parts and accessories through dealers, while Ford Pro combines commercial vehicles with fleet software, charging and maintenance services; Ford Credit earns money from customer and dealer financing and leases. Connected services add subscriptions for vehicle features and business operations. Founded by Henry Ford in 1903, the company is headquartered in Dearborn, Michigan.

Company size
10,001+
Company stage
IPO
Headquarters
Dearborn, MI
Founded
1903

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