Industrial Engineer
Factorial Energy
| Company | Factorial Energy |
| Category | Engineering |
| Location | Cheonan |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 27 May 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Who We Are
Factorial Energy is a pioneering U.S.-based solid-state battery company driving the future of energy storage and electrification. Partnered with global leaders including Mercedes-Benz, Stellantis, Hyundai, and Kia, Factorial is at the forefront of developing next-generation e-mobility platforms for commercial, defense, and consumer applications—spanning electric vehicles (EVs), drones, eVTOL aircraft, power tools, marine systems, robotics, and more. The company has achieved multiple industry firsts, including being the first to power a demonstration vehicle with a global OEM (Mercedes- Benz) which achieved over 1,200 km (749 mi) of range, and the first to earn UN 38.3 certification for automotive-sized lithium-metal solid-state cells, the first to deliver B-samples of automotive-sized solid-state batteries to major OEMs.
The Opportunity:
Factorial Energy is seeking an Industrial Engineer to join our team in our Cheonan, South Korea, location. This person will be responsible for driving manufacturing efficiency, cost reduction, and operational excellence across our consumer battery production lines. This role spans four core IE disciplines: lean production improvement, capacity planning & facility layout, time study & cost engineering, and data-driven continuous improvement. The Ideal candidate will work closely with Manufacturing, Process Engineering, Supply Chain, and Finance teams to optimize workflows, eliminate waste, and ensure our lines scale effectively with business growth. The ideal candidate is both analytically rigorous and practically hands-on , comfortable on the factory floor as well as in front of a data model.
In this role, you will:
Lead and facilitate Kaizen events, Value Stream Mapping (VSM) workshops, and waste elimination projects across electrode, assembly, formation, and packaging lines
Identify and eliminate the 8 wastes (overproduction, waiting, transport, over-processing, inventory, motion, defects, unused talent) to improve throughput and reduce cycle time
Implement and sustain 5S, visual management, and standard work practices on the production floor
Drive OEE (Overall Equipment Effectiveness) improvement initiatives by analyzing availability, performance, and quality loss data to prioritize high-impact actions
Mentor operators and line leaders in lean thinking and problem-solving tools (A3, 5-Why, fishbone analysis)
Develop and maintain capacity models for all production lines, providing data-driven recommendations for equipment investment, shift expansion, and bottleneck resolution
Plan and optimize factory floor layouts using simulation tools (e.g., AutoCAD, Arena, or Flexsim) to minimize material travel distance, improve flow, and support new product introduction (NPI)
Collaborate with the project team on new line setup and ramp-up, ensuring layout, equipment placement, and ergonomics meet both production and safety requirements
Track and report capacity utilization, identifying risks to on-time delivery and proposing mitigation plans in alignment with Production Planning and Sales Operations
Conduct time studies (stopwatch, video-based) and establish standard times for all operations across the battery manufacturing process (coating, winding/stacking, assembly, formation, testing, packaging)
Build and maintain standard cost models, including direct labor, indirect labor, and overhead allocation, to support product pricing, cost-down initiatives, and make-vs-buy analyses
Analyze labor efficiency, calculate manpower requirements for each production segment, and develop staffing plans aligned with production schedules
Partner with Finance and Operations leadership to track actual vs. standard cost variances and identify root causes of cost overruns
Collect, clean, and analyze production data from MES, ERP, and equipment systems to identify