Lead MEMS Timing Product Engineer — DOE & High-Volume Yield

Niuro; Santa Clara, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Niuro in Santa Clara, CA seeks a Principal Product Engineer to lead MEMS timing product development, yield optimization, and deployment for high-volume manufacturing. You will drive data-driven improvements across process, voltage, and temperature stresses and work with foundry, assembly, and test partners to ensure robust releases.

You will guide design of experiments, analyze large datasets with Exensio/JMP/MATLAB/Python, and collaborate with cross-functional teams to deliver reliable MEMS

Qualifications

• 8+ years of experience in Product Engineering, Semiconductor Device Engineering, or MEMS.
• Bachelor’s or Master’s degree in a technical field as listed.
• Proficiency in data analysis tools (Exensio, JMP, MATLAB, Python).

Responsibilities

• Lead product engineering from concept through high-volume ramp for MEMS oscillators and timing ICs.
• Analyze large datasets to assess performance across process, voltage, temperature, and reliability stresses.
• Partner with test engineering to design, develop, and deploy production test solutions.
• Drive root-cause analysis and problem-solving for device performance and yield issues.
• Implement DOE to optimize parameters, improve yield, and reduce test costs.
• Collaborate with foundry, assembly, and test partners to resolve process and equipment issues.

Skills

8+ years experience

Python

MATLAB

Exensio

JMP

Education

Bachelors or Masters in Electrical, Mechanical, Materials Science, or Physics

Tools

Exensio

JMP

MATLAB

Python

Job description

Niuro in Santa Clara, CA seeks a Principal Product Engineer to lead MEMS timing product development, yield optimization, and deployment for high-volume manufacturing. You will drive data-driven improvements across process, voltage, and temperature stresses and work with foundry, assembly, and test partners to ensure robust releases.

You will guide design of experiments, analyze large datasets with Exensio/JMP/MATLAB/Python, and collaborate with cross-functional teams to deliver reliable MEMS