Scientist II, Silicon Photonics
Lila Sciences · Cambridge, MA USA · Alewife, Cambridge, MA
CHECKED 14H AGO
Bio & Science AIonsitemid-level$128k–$170k
At a glance
Highlights
- Own full-stack characterization from thin films to electro-optic modulators.
- Build the measurement foundation turning novel materials into trusted data.
- Prototype wafer-level methods to scale into reliable automation infrastructure.
What they offer
- Bonus potential
- Early-stage equity
- Medical, dental and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with company holidays
- Paid parental leave
- Educational assistance program
- Commuter benefits and subsidized lunch
Ideal candidate
Hands-on experimentalist who has followed photonic devices from material to test and obsesses over measurement quality. You thrive at the intersection of materials, fabrication, and modeling, turning ambiguous data into trusted decisions.
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
- Experience measuring thin-film optical and electro-optic properties including electro-optic coefficients
- Experience testing passive photonic structures 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
- Experience developing measurement methods where no standard protocol exists
- Familiarity with high-speed RF/electronics, fiber optics, and electro-optic testing workflows
- Proficiency in Python, MATLAB, or equivalent for automation and data analysis
- Ability to work across design, fabrication, simulation, and automation teams
Lab profile
About Lila Sciences
Building an autonomous science platform where AI, automation, and biology co-evolve for medicine and materials.
What they build
- Autonomous Science Platform
- AI-designed biologics validated in wet-lab
- Electro-optic materials and photonic devices
Known for
- Large-scale automated data generation
- High-throughput protein purification and analytics
- Protein design and BioML modeling
- Robotic orchestration and lab simulation