Saronic
Industrial Engineer
About this role
Saronic Technologies seeks an Industrial Engineer to optimize manufacturing and operational processes for autonomous surface vessel production. You'll apply lean manufacturing, Six Sigma, and data analytics to improve efficiency, reduce waste, and enhance cost-effectiveness while collaborating with cross-functional teams in a fast-paced maritime environment.
What you'll do
- Analyze and optimize material flow across manufacturing processes for autonomous surface vessels
- Implement lean manufacturing and Six Sigma methodologies to reduce waste and improve cycle times
- Conduct data analysis to generate actionable insights for process improvements
- Develop production workflows ensuring efficient utilization of materials, components, and labor
- Identify and resolve bottlenecks, quality issues, and inefficiencies in production
- Collaborate with engineering, design, and operations teams on manufacturability optimization
What they're looking for
- Lean manufacturing and Six Sigma methodologies
- Data analysis (Excel, Minitab, statistical software)
- Material flow analysis and optimization
- Production planning and workflow design
- Process improvement (Kaizen, continuous improvement)
- Root cause analysis and problem-solving
- Cross-functional team collaboration
- KPI and performance metrics development
Benefits
- Comprehensive medical insurance (100% employee, 80% dependent premium coverage)
- Dental and vision insurance (100% basic employee, 80% dependent coverage)
- Generous PTO and holiday time
- Paid parental leave (maternity and paternity)
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Saronic
Saronic builds autonomous maritime systems and vessels equipped with advanced imaging, software, and electro-mechanical components. The company is hiring quality engineers, software engineers, graphics programmers, optomechanical engineers, and manufacturing engineers to develop and manufacture reliable autonomous maritime operations.
View all jobs at SaronicLikely interview questions
- Describe a lean or Six Sigma project you led and quantify the improvements you achieved
- How have you used data analysis tools to identify and solve manufacturing bottlenecks?