Manager Design Engineering, Battery Modeling

Milwaukee Tool•Brookfield, WI

About The Position

The primary responsibility of the Manager, Design Engineering – Battery Modeling is to build and lead a simulation team that guides the design, development, validation, and delivery of high-power-density lithium-ion battery packs. This role combines people leadership, advanced modeling and simulation expertise, technical strategy, and project portfolio management to improve product performance, safety, reliability, cost, and development speed.

Requirements

Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Engineering Mechanics, Materials Science, Chemical Engineering, or a related technical field
Seven or more years of relevant modeling, simulation, product development, or validation experience.
Two or more years of demonstrated technical team leadership; direct people-management experience preferred.
Demonstrated ability to lead, coach, and develop a team of three to five engineers with varying levels of simulation experience.
Strong experience with ANSYS simulation tools
Experience developing and validating structural, thermal, electro-thermal, durability, or coupled multiphysics models.
Demonstrated experience with simulation-to-test correlation, material characterization, model calibration, and assessment of model accuracy.
Experience with Python, MATLAB scripting, workflow automation, optimization, Design of Experiments, or statistical analysis.
Working knowledge of lithium-ion cells, battery-pack architecture, battery safety, durability, thermal management, and product validation practices.
Strong understanding of 3D CAD tools such as SolidWorks, Siemens NX, or equivalent platforms.
Strong analytical, project planning, and communication skills, including the ability to explain complex technical information to technical and nontechnical stakeholders.
Ability to travel up to 10%, including domestic and international travel.

Nice To Haves

Experience with Altair HyperWorks, LS-DYNA, Abaqus, MATLAB/Simulink, or equivalent platforms is beneficial.
Interest in tools used in the construction trades.

Responsibilities

Build, lead, coach, and develop a team of simulation engineers supporting multiple battery development programs.
Serve as the technical leader for battery-pack modeling and simulation, providing clear recommendations to Project Leaders and Global Engineering teams to support design trade-off decisions.
Own and execute the battery modeling and simulation technical roadmap, including methods, tools, computing resources, validation strategy, and capability development.
Prioritize simulation work across programs based on technical risk, business impact, timing, and available resources.
Establish modeling standards, review practices, documentation requirements, correlation targets, and simulation quality metrics for components, assemblies, and battery packs.
Balance simulation and physical testing to support battery development, qualification, and risk reduction.
Drive correlation of analytical models to component-, assembly-, and pack-level testing; continuously improve model accuracy and predictive capability.
Partner with Battery Systems, Pack Design, Electronics, Test, Reliability, Manufacturing, and Program Management teams to translate simulation results into actionable design decisions.
Develop and deploy scalable, automated simulation workflows that support design exploration, optimization, Design of Experiments, and rapid design iteration.
Communicate technical risks, assumptions, limitations, recommendations, and trade-offs to engineering and executive leadership.
Support recruiting, performance management, career development, workload planning, and technical succession for the simulation team.
Execute and oversee engineering analyses using the following tools and methods: 0D and 1D system simulation using MATLAB/Simulink or equivalent tools, Structural, thermal, electro-thermal, durability, and coupled Multiphysics simulation using ANSYS, Altair, or equivalent tools, Design of Experiments, optimization, and parametric studies, Statistical data analysis, model calibration, and simulation-to-test correlation.