Manufacturing Engineer: Lead Lean Process Improvements

Bosch; Florence (KY); Sur place; USD 75 000 - 110 000; Plein temps

Avantages offerts par ce poste

Health benefits

401(k) matching

Paid time off

Résumé du poste

Bosch is seeking a Manufacturing Engineer to support planning of new equipment and processes in the Electric Rack Steering assembly area. The role collaborates with Process Engineering, Operations, Quality, and Logistics to meet Safety, Quality, Cost and Delivery targets.

The candidate should be self-driven, prioritize work by business impact, and use data to make decisions in a fast-paced manufacturing environment.

Qualifications

• Bachelor's degree in Engineering; 5+ years in automotive manufacturing or related field.
• Experience with assembly processes (pressing, torqueing, testing).
• Ability to lead and implement projects (new, change requests, etc.).
• Strong presentation and communication skills across functions.

Responsabilités

• Own daily performance of assigned manufacturing lines including safety, quality, delivery, and cost.
• Identify and implement improvements to safety, quality, productivity, and equipment reliability.
• Lead structured problem-solving (PDCA, 5 Why, Fishbone, Six Sigma) to root causes and corrective actions.
• Analyze production data to identify trends and drive continuous improvement.
• Drive Lean manufacturing principles and maintain APQP documentation.
• Collaborate with Quality, Operations, and Logistics to meet targets.

Connaissances

Manufacturing engineering

Lean manufacturing

Six Sigma

Problem solving

Data analysis

Cross-functional collaboration

Formation

Bachelor's degree in Engineering

Outils

PFMEA

Control Plans

SPC

IATF 16949

Description du poste

Bosch is seeking a Manufacturing Engineer to support planning of new equipment and processes in the Electric Rack Steering assembly area. The role collaborates with Process Engineering, Operations, Quality, and Logistics to meet Safety, Quality, Cost and Delivery targets.

The candidate should be self-driven, prioritize work by business impact, and use data to make decisions in a fast-paced manufacturing environment.