
Automotive manufacturer
IMG Material Flow and Packaging Engineer
-
Deliver minimum 2 assigned MFPE projects (DRI) per year
-
Proactively engage in upfront engineering activities by working closely with Advance MFPE teams pre
-
Support effective handover from Advance MFPE to Implementation MFPE for all approved programs post
. -
Effective handover from Implementation to plant team
-
Execute Material Flow & Packaging deliverables aligned with program timing, quality, and cost targets across BPS, TCF, Warehouse for FTM, AAT, and FVL.
-
Review, evaluate, and validate packaging designs (PKG) in collaboration with suppliers and study teams.
-
Ensure packaging designs are manufacturable, robust, cost‑effective, and meet GPP approval requirements.
-
Be responsible for internal dunnage and supplier packaging design and delivery before TT phase.
-
Develop and execute layout and material flow solutions to ensure efficient, safe, and ergonomic operations for overlap timing and MP1 onward
-
Lead CLL for enterprise cost optimization both pre
and post
. -
Ensure approved funding is utilized efficiently and in line with program assumptions and target date.
-
Proactively identify, propose, and execute improvement and cost‑saving initiatives, including TVM projects.
-
Support value optimization activities even when outside initially approved funding scope.
-
Raise Purchase Requisitions (PR) / Purchase Orders (PO) and track supplier delivery performance, timelines, and technical compliance.
-
Support resolution of packaging quality, timing, or performance concerns.
-
Work closely with Advance MFPE, Launch, NMP, VME, Plant MPL, Plant TCF, IT, Maintenance, and other cross‑functional teams using a “One Team” mindset.
-
Provide MFPE technical input to support launch readiness and production stability.
-
Strong safety‑first mindset in all engineering solutions.
-
Ensure all new equipment, layouts, and packaging solutions comply with safety and ergonomic standards, targeting no SRA > 6.
-
Contribute to improved Launch Quality through standardized and best‑practice packaging implementation.
-
Support continuous improvement to enhance operational robustness and material flow efficiency.
-
Improved launch quality and stable production ramp‑up
-
Optimized enterprise cost through effective packaging and material flow engineering
-
Strong cross‑functional collaboration and technical contribution across ASEAN plants
-
Bachelor’s degree in Engineer
-
Mechanical, Electrical, Mechatronic, Robotics, Data analytics
-
3-8 Years working experience in automotive company
-
AGV/AMR/ASRS/Conveyor/RFID/Vision system/Digitalization/Data analytic
-
Strong analytical capability, logical thinking, and structured problem‑solving skills.
-
Ability to analyze data, identify root causes, and propose practical engineering solutions
-
Very good command of English, both written and verbal.
-
Proficient in standard computer tools (e.g., MS Office); experience with engineering or data tools is a plus.
Top four Professional/Organizational Competencies required
-
Flexsim/Simulation tool
-
Autocad/Teamcenter
-
Power app /Power BI/ Power automate
-
PFEP
-
Deliver minimum 2 assigned MFPE projects (DRI) per year
-
Proactively engage in upfront engineering activities by working closely with Advance MFPE teams pre
-
Support effective handover from Advance MFPE to Implementation MFPE for all approved programs post
. -
Effective handover from Implementation to plant team
-
Execute Material Flow & Packaging deliverables aligned with program timing, quality, and cost targets across BPS, TCF, Warehouse for FTM, AAT, and FVL.
-
Review, evaluate, and validate packaging designs (PKG) in collaboration with suppliers and study teams.
-
Ensure packaging designs are manufacturable, robust, cost‑effective, and meet GPP approval requirements.
-
Be responsible for internal dunnage and supplier packaging design and delivery before TT phase.
-
Develop and execute layout and material flow solutions to ensure efficient, safe, and ergonomic operations for overlap timing and MP1 onward
-
Lead CLL for enterprise cost optimization both pre
and post
. -
Ensure approved funding is utilized efficiently and in line with program assumptions and target date.
-
Proactively identify, propose, and execute improvement and cost‑saving initiatives, including TVM projects.
-
Support value optimization activities even when outside initially approved funding scope.
-
Raise Purchase Requisitions (PR) / Purchase Orders (PO) and track supplier delivery performance, timelines, and technical compliance.
-
Support resolution of packaging quality, timing, or performance concerns.
-
Work closely with Advance MFPE, Launch, NMP, VME, Plant MPL, Plant TCF, IT, Maintenance, and other cross‑functional teams using a “One Team” mindset.
-
Provide MFPE technical input to support launch readiness and production stability.
-
Strong safety‑first mindset in all engineering solutions.
-
Ensure all new equipment, layouts, and packaging solutions comply with safety and ergonomic standards, targeting no SRA > 6.
-
Contribute to improved Launch Quality through standardized and best‑practice packaging implementation.
-
Support continuous improvement to enhance operational robustness and material flow efficiency.
-
Improved launch quality and stable production ramp‑up
-
Optimized enterprise cost through effective packaging and material flow engineering
-
Strong cross‑functional collaboration and technical contribution across ASEAN plants
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Ford 소개

Ford
PublicThe Ford Motor Company is an American multinational automobile manufacturer headquartered in Dearborn, Michigan, United States. It was founded by Henry Ford and incorporated on June 16, 1903.
10,001+
직원 수
Dearborn
본사 위치
$48B
기업 가치
리뷰
10개 리뷰
3.7
10개 리뷰
워라밸
3.8
보상
4.2
문화
3.5
커리어
3.2
경영진
2.8
68%
지인 추천률
장점
Good benefits and compensation
Work-life balance and flexibility
Supportive colleagues and positive environment
단점
Poor management and communication
Limited career advancement
High workload and stress
연봉 정보
21개 데이터
Mid/L4
Senior/L5
Mid/L4 · ADAS Data Analytics Engineer
1개 리포트
$132,847
총 연봉
기본급
$102,190
주식
-
보너스
-
$132,847
$132,847
면접 후기
후기 3개
난이도
3.0
/ 5
소요 기간
14-28주
경험
긍정 0%
보통 67%
부정 33%
면접 과정
1
Application Review
2
Phone Screening
3
Technical Interview
4
Team Interview
5
Offer
자주 나오는 질문
Technical Knowledge
Behavioral/STAR
Past Experience
Coding/Algorithm
최근 소식
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·
1w ago
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1w ago
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1w ago