Advanced Manufacturing Engineer DFM (m/f)

A global, innovation-driven organization operating in a highly regulated and quality-focused industry. The company develops advanced technology solutions and collaborates with international partners to deliver scalable, high-performance products. It emphasizes engineering excellence, continuous improvement, and cross-functional collaboration across the full product lifecycle.

• Bachelor’s degree in Engineering (Mechanical, Electrical, Biomedical, or related field).
• Proven experience in manufacturing, preferably within regulated or high-quality industries.
• Strong knowledge of Lean Manufacturing and Six Sigma methodologies (certification is an advantage).
• Experience with statistical tools and data analysis (e.g., DOE, SPC, capability analysis).
• Understanding of manufacturing processes related to electronics and/or flexible materials is a plus.
• Familiarity with quality standards and regulatory requirements is beneficial.
• Strong communication and teamwork skills with the ability to work in cross-functional environments.
• Ability to manage multiple priorities and work effectively under time constraints.
• Fluent English (minimum C1 level).

• Collaborate with design teams to ensure products are optimized for manufacturability and scalable production.
• Conduct detailed Design for Manufacturability (DFM) reviews covering product design, processes, and tooling.
• Plan and execute prototype builds, process validations, and documentation (e.g., PFMEA, control plans).
• Drive implementation of Lean Manufacturing, Six Sigma, and continuous improvement initiatives.
• Analyze cost vs. performance trade-offs and provide data-driven recommendations.
• Work with internal teams and external suppliers to assess manufacturing capabilities and introduce new processes or equipment.
• Support supplier interactions, audits, and process development activities.
• Contribute to development of manufacturing processes for both flexible materials and electronic assemblies.
• Participate in design of experiments (DOE) and establish robust, repeatable process windows.