R&D Process Engineer — Lean Innovation & Optimization

Carlisle Companies Incorporated

Carlisle, Northern (Cumberland County, KY)

Híbrido

USD 110.000 - 150.000

Jornada completa

14 días+

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Descripción de la vacante

RadNet, Inc. is seeking an experienced R&D Process Engineer to advance manufacturing processes that improve product quality, boost productivity, and cut operating costs across our operations.

You will lead cross-functional projects with Operations, Quality, Engineering, and R&D to implement new technologies and process controls from concept to execution. You will mentor teams, apply Lean and Six Sigma methods, and use data to drive improvements in process capability and cost efficiency in a

Formación

  • Bachelor's degree in Engineering or Science.
  • 5+ years of experience in process engineering within plastics, rubber, chemical, or related manufacturing industries.
  • Strong knowledge of plastic compounding, extrusion, web handling, coating, winding, and manufacturing process technologies.
  • Experience with quality and continuous improvement tools including SPC, DOE, Gauge R&R, DMAIC, Lean, and Six Sigma.
  • Proven ability to lead cross-functional projects, influence stakeholders, and solve complex manufacturing problems.
  • Strong communication, project management, and analytical skills.
  • Experience with SAP, Microsoft Office, and manufacturing process control systems is preferred.

Responsabilidades

  • Lead complex process improvement initiatives from concept through execution.
  • Develop, optimize, and implement manufacturing processes to improve quality and reduce costs.
  • Mentor production and engineering teams.
  • Champion continuous improvement using Carlisle Operating System principles.
  • Partner with Operations, Quality, Engineering, and R&D to develop new technologies and support production.
  • Lead capital and process improvement projects.

Conocimientos

Process engineering
Lean manufacturing
Six Sigma
SPC
DOE
DMAIC
Cross-functional collaboration
Communication skills
Project management
Analytical skills
Manufacturing data analysis
Microsoft Office
Manufacturing process controls

Educación

Bachelor's degree in Engineering or Science

Herramientas

SAP
Manufacturing process control systems

Descripción del empleo

We're seeking an experienced R&D Process Engineer to join our team and help develop, optimize, and implement manufacturing processes that improve product quality, increase productivity, and reduce operating costs across our operations.

In this role, you'll lead complex process improvement initiatives, applying advanced analytical methods, experimental design, and Lean manufacturing principles to solve technical challenges and drive measurable business results. You'll partner closely with Operations, Quality, Engineering, and R&D to develop new technologies, support production, implement process controls, and lead capital and process improvement projects from concept through execution.

As a technical leader, you'll troubleshoot high-impact manufacturing issues, establish process control strategies, mentor production and engineering teams, and champion continuous improvement using Carlisle Operating System principles. You'll also leverage manufacturing data and quality systems to identify opportunities, improve process capability, and ensure consistent product performance.

What You'll Bring

  • Bachelor's degree in Engineering or Science
  • 5+ years of experience in process engineering within plastics, rubber, chemical, or related manufacturing industries.
  • Strong knowledge of plastic compounding, extrusion, web handling, coating, winding, and manufacturing process technologies.
  • Experience with quality and continuous improvement tools including SPC, DOE, Gauge R&R, DMAIC, Lean, and Six Sigma.
  • Proven ability to lead cross-functional projects, influence stakeholders, and solve complex manufacturing problems.
  • Strong communication, project management, and analytical skills.
  • Experience with SAP, Microsoft Office, and manufacturing process control systems is preferred.

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