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Salary: USD 128,000 - 170,000 / annual
Lila Sciences is building Scientific Superintelligence to accelerate discovery across medicine, materials, and energy. The Scientist II, Silicon Photonics role sits within the Materials Science team of the Autonomous Science Platform, owning the measurement, analysis, and data-quality foundation for novel electro-optic materials and photonic devices.
You will own characterization across the full stack: thin-film material properties, passive photonic structures, and electro-optic modulators at both chip and wafer level. This is hands-on work—you will assemble, debug, and calibrate optical and optoelectronic measurement setups, not just operate them. You will define what to measure, design test setups, and establish calibration and quality-control procedures that make results comparable across material variants, process conditions, and design iterations.
The role bridges materials, device design, fabrication, and test. You will interpret measured data in the context of material properties, process variation, and device physics; feed findings back into material and design decisions; and partner with simulation and ML teams. You will also define measurement requirements for the automation team and prototype methods well enough to scale into reliable infrastructure.
Key responsibilities include:
• Own characterization spanning thin-film material properties, passive photonic structures, and electro-optic modulators at chip and wafer level.
• Define measurement strategies that produce reliable, decision-grade material and device performance data.
• Design, assemble, calibrate, and debug optical and optoelectronic test setups.
• Create measurement methods for novel thin-film materials where no standard protocol exists, with calibration and quality-control practices.
• Develop wafer-level measurement approaches that provide statistical insight into material and process variation.
• Analyze data through material properties, device physics, process variation, and measurement uncertainty.
• Feed characterization results back into material, design, and fabrication decisions; partner with simulation and ML teams.
• Prototype measurement methods for the automation team to scale into reliable infrastructure.
• Document procedures, data standards, and measurement limitations for cross-functional teams.
Requirements:
• PhD in Electrical Engineering, Applied Physics, Materials Science, or related field.
• Hands-on experience characterizing photonic materials and devices at chip and wafer level, spanning thin-film and material-level measurements through passive and active device testing.
• Experience measuring thin-film optical and electro-optic properties, including extraction of electro-optic coefficients.
• Experience testing passive photonic structures such as waveguides, resonators, and couplers, including loss and dispersion characterization.
• Experience with electro-optic modulators or related active integrated photonic devices.
• Experience building and debugging optical and optoelectronic measurement setups, including alignment, calibration, and noise control.
• Experience developing measurement methods where no standard protocol exists, including defending measurement validity and data quality.
• Experience interpreting data through material properties, device physics, process variation, measurement uncertainty, and repeatability.
• Familiarity with high-speed RF/electronics, fiber optics, and electro-optic testing workflows.
• Proficiency in Python, MATLAB, or equivalent language for automated workflow and data analysis, and collaboration with ML and automation teams.
• Ability to work across design, fabrication, simulation, and automation teams while owning the measurement-quality standard.
Bonus experience:
• Characterizing novel, heterogeneous, or hybrid electro-optic materials integrated on silicon photonics (χ⁽²⁾ or Pockels-effect thin films).
• Correlating film-level material properties to device-level performance.
• Hands-on cleanroom fabrication experience.
• Wafer-level photonic probing, active alignment, foundry workflows.
• Waveguide and electro-optic modulator simulation tools (Lumerical, COMSOL, or equivalent).
• Test automation, instrument control software, or measurement data pipelines.
• Supplying measurement data to ML, modeling, or simulation teams.
