Automation Engineer

Key Responsibilities

Analyze production data to identify yield cycle time and cost improvement opportunities on assigned manufacturing lines.

Plan and execute Lean Six Sigma and TPM projects from DOE design through implementation and results validation as part of the sites Operational Excellence roadmap.

Build and deploy machine learning models for manufacturing use cases e.g. yield prediction computer-vision defect detection and anomaly/excursion detection in partnership with Data Science/IT.

Develop real-time dashboards automated reports and data pipelines that give engineers and operators faster visibility into process performance.

Support automation and Industry 4.0 initiatives MES integration IIoT sensor deployment and robotics/automated material handling from pilot through production rollout.

Maintain and improve statistical process control (SPC) systems monitoring process capability (Cpk) and flagging out-of-control conditions.

Investigate process-related yield and quality excursions using structured root-cause methods (8D DMAIC FMEA) and implement corrective/preventive actions.

Support process qualification and control plans for new product introduction (NPI) and process changes.

Partner with Equipment/Maintenance and Quality teams to troubleshoot equipment-related process issues.

Document standard work process specifications and lessons learned to support knowledge transfer and training.

Present project results and improvement recommendations to the Process Engineering Manager and cross-functional stakeholders.

Qualifications :

Required Qualifications

Bachelors degree in Industrial Manufacturing Electrical Mechanical or SW Engineering Computer Science or a related technical field.

25 years of experience in manufacturing process or industrial engineering ideally in semiconductor or electronics manufacturing.

Hands-on experience with Lean Six Sigma tools (DOE root-cause analysis value stream mapping); Green Belt or working equivalent preferred.

Practical experience building or deploying machine learning models (e.g. classification regression computer vision) using Python and common ML libraries.

Working knowledge of statistical process control (SPC) process capability (Cpk) analysis and data visualization tools.

Strong data analysis skills (Python SQL Minitab JMP or Excel/Power BI at minimum).

Comfortable working directly on the shop floor with equipment operators and production data.

Additional Information :

Renesas is an embedded semiconductor solution provider driven by its Purpose To Make Our Lives Easier. With a global team of over 21000 engineers and problem solvers in more than 30 countries we offer the opportunity to work on worldleading technology for Automotive Industrial Infrastructure and IoT shaping a safer healthier greener and smarter future.

At Renesas TAGIE is our culture grounded in being Transparent Agile Global Innovative and Entrepreneurial. It shapes how we work grow and deliver on our purpose together. This collaborative spirit and mindset drive our semiconductor technology to transform industries and impact millions of lives.

We believe in rewarding our employees with a competitive benefits package alongside their salary. More information will be provided during the hiring process.

Are you ready to join our team and shape the future with us

Renesas Electronics is an equal opportunity and affirmative action employer committed to supporting diversity and fostering a work environment free of discrimination on the basis of sex race religion national origin gender gender identity gender expression age sexual orientation military status veteran status or any other basis protected by law. For more information please read our Diversity & Inclusion Statement.

Remote Work :

No

Employment Type :

Full-time