Process Engineer (Optical Polishing)

About the role

The Process Engineer will lead the development and optimisation of chemical‑mechanical polishing (CMP) and fine‑grinding processes for zinc selenide (ZnSe) optical components. You will work closely with production, quality and safety teams to ensure high‑performance optical surfaces that meet stringent standards.

Key responsibilities

• Develop and optimise CMP parameters (abrasive type, pressure, speed, slurry composition, pH, temperature) to minimise surface haze, scratches and subsurface damage.
• Implement statistical process control (SPC) and define quality criteria based on interferometry, flatness and roughness specifications (ISO 10110, MIL‑PRF‑13830B).
• Maintain and improve lapping/polishing equipment, evaluate new tools, pads and slurries, and create predictive maintenance programmes.
• Conduct failure analysis using optical microscopy, interferometry and SEM; perform root‑cause investigations and corrective actions.
• Introduce automation and Industry 4.0 solutions for real‑time monitoring and standard work procedures.
• Ensure environmental and safety compliance for ZnSe handling, waste management and risk assessments (FMEA, HAZOP).

Required profile

• Bachelor’s degree in Materials Science, Mechanical, Optical or Manufacturing Engineering.
• 1‑3 years experience in precision optics polishing, CMP or semiconductor wafer processing.
• Strong knowledge of ZnSe material behaviour, ISO 10110 optical surface specifications and relevant MIL standards.
• Familiarity with metrology tools such as interferometers, profilometers, AFM and SEM.
• Preferred: Six Sigma Green/Black Belt, experience with precision optics (lenses, IR windows, laser optics), fluid‑dynamics of polishing slurries.

Required skills

• ZnSe polishing and CMP techniques
• Abrasive selection (CeO₂, Al₂O₃, diamond) and slurry formulation
• pH and temperature control
• Statistical Process Control (SPC) and Design of Experiments (DOE)
• Interferometry and optical metrology
• Lapping/polishing equipment operation and predictive maintenance
• Failure analysis using optical microscopy and SEM
• Automation scripting (Python, MATLAB, LabVIEW)
• Six Sigma (Green/Black Belt)