Position Overview:
We are seeking a highly motivated and skilled Additive Manufacturing Engineer to join our team, specializing in Wire Arc Additive Manufacturing (WAAM) and Laser Powder Bed Fusion (LPBF). The successful candidate will play a key role in developing, optimizing, and scaling additive manufacturing processes for industrial applications, contributing to innovation and operational excellence.
Key Responsibilities:
- Lead and execute additive manufacturing projects using WAAM and LPBF technologies.
- Develop process parameters and optimize build strategies for various materials.
- Operate and maintain WAAM and LPBF equipment, ensuring high-quality output and machine reliability.
- Perform design for additive manufacturing (DfAM), including part redesign and topology optimization.
- Conduct post-processing activities such as heat treatment, machining, and surface finishing.
- Collaborate with cross-functional teams including design, quality, and production to integrate AM parts into final products.
- Analyze build data and perform root cause analysis for defects and process deviations.
- Ensure compliance with safety standards, quality protocols, and industry regulations.
- Document process workflows, technical reports, and best practices.
Qualifications:
- Bachelor's degree in Mechanical Engineering, Materials Science, or related field.
- Proven experience in additive manufacturing, specifically WAAM and LPBF.
- Strong understanding of metallurgy, thermal processes, and mechanical properties of AM materials.
- Proficiency in CAD software and simulation tools (e.g., SolidWorks, ANSYS).
- Familiarity with AM standards and certification requirements (e.g., ASTM, ISO).
- Excellent problem-solving skills and attention to detail.
- Strong communication and teamwork abilities.
Preferred Skills:
- Experience with robotic systems and automation in WAAM.
- Knowledge of powder handling and safety protocols.
- Background in aerospace, automotive, or energy sectors.
- Experience with data analytics and machine learning in AM process optimization.
