Job Description

As a Staff Manufacturing Automation Engineer at Nokia's Allentown facility, you will support efficient, high-quality, high-volume production of next-generation optical transceivers. This is an experienced technical role for an engineer who has designed, deployed, and scaled automation for precision electronics manufacturing. You will collaborate with a team of automation engineers to develop systems for advanced test and packaging processes, and have hands-on technical responsibility for machine vision, robotics, and process integration as we scale capacity and continuously improve.

You will partner with the Product and Process Engineering and Manufacturing Operations teams, all passionate about innovation in optical communication. Your work environment is supportive and collaborative, encouraging cross-functional teamwork to drive excellence in execution. You will thrive in a data-driven culture, employing your experience with process automation for advanced packaging and testing, AI-driven machine vision, robotics, and analytical skills to drive continuous improvement in productivity and yield. Benefits include a structured career progression pathway, exposure to cutting-edge technology like the Infinite Capacity Engine, and opportunities to leverage AI. Enjoy a collaborative atmosphere that values your insights and fosters professional growth in a leading-edge industry.

• Design, develop, and implement automation systems for advanced test and packaging cells for precision electro-optical (photonic) device manufacturing.
• Integrate AI-based machine vision systems for defect detection, precision alignment, in-line inspection, and statistical process control.
• Support manufacturing quality and capacity requirements and continuous improvement initiatives.
• Partner with product, test, and process engineering teams to identify opportunities that improve yield, throughput, and cycle time.
• Support root cause investigation and resolution of complex automation equipment issues impacting production output.
• Partner with vendors and integrators of vision hardware, robotics, and automation to develop designs and drive successful implementation.
• Develop and maintain documentation, specifications, and validation protocols for automated systems in a regulated manufacturing environment.
• Support capital equipment justification and capacity planning for automation investments.

Must-Have:

• BS Degree in science or engineering (Electrical, Mechanical, Physics, or related); MS Degree preferred.
• 5 or more years of experience designing and deploying industrial automation systems in a high-precision, high-volume manufacturing environment.
• Hands-on experience integrating machine vision systems, including AI/deep learning-based inspection (e.g. defect classification, automated optical alignment.)
• Demonstrated experience in robotics, motion control, or precision mechanical system design and integration.
• Demonstrated ability to implement automation systems, from concept through qualification, integration, and production ramp.
• Experience working directly with controls/PLC systems, machine vision software (e.g. Cognex, Keyence, or similar) and industrial communication protocols.
• Familiarity with SQL and statistical processing software (e.g., JMP/JSL, Minitab) and SPC considerations.
• Hands-on, curious, collaborative problem-solving approach.
• Experience creating detailed reports, engineering documentation, presentations, and facilitating design reviews.

Nice-To-Have:

• Direct experience automating advanced test and/or packaging processes for electro-optical, photonic, semiconductor, or similarly high precision products.
• Experience with custom vision model development or training (e.g. convolutional neural networks for defect detection)
• Demonstrated history of innovation in automation or precision manufacturing.
• Experience supporting new product introduction (NPI) and capacity ramp alongside automation development.
• Familiarity with statistical process control (SPC), DFM/DFA, and Six Sigma or Lean manufacturing methodologies.