RF Filter Design Co‑Op: Data-Driven, Hands-On Innovation

Skyworks Solutions, Inc.; Irvine (CA); On-site; USD 36,000 - 66,000; Full time

Job summary

Skyworks Solutions, Inc. in Irvine is seeking a Winter/Spring 2027 Co-op on the Filter Design team.

You will work with RF professionals to improve acoustic filters (SAW/BAW) and contribute to data-driven analysis and design automation. This on-site, six-month program invites PhD or Master’s students in engineering or related fields to apply mathematical algorithms, statistics, and machine learning to real-world filter design challenges, under mentorship.

Qualifications

• PhD or Master's in Mechanical Eng, Electrical Eng, CS, Math, Physics, or related field.
• Ability to work on-site in Irvine for 6 months.
• Experience with the design, development, and software implementation of complex mathematical algorithms.
• Knowledge of statistics and machine learning methods.
• Coursework in the theory and applications of circuit design/acoustic filters.
• Great communication skills and the ability to understand the requests from the filter design team.
• Quick learner and interest in cutting-edge technology.
• Well organized and detail oriented.

Responsibilities

• Implement and recommend data-driven solutions to analyze BAW resonators/filters with guidance from senior engineers.
• Design automation and implementations to improve filter design efficiency and data plots.
• Work closely with the filter design team and IT/modeling team to bridge requests and implement them in the design tool/utility/methodology.

Skills

Data-driven analysis

Communication skills

Fast learner

Attention to detail

Team collaboration

Cutting-edge technology interest

Education

PhD or Master's in Mechanical Eng / E.E. / CS / Math / Physics or related field

Tools

Python

MATLAB

Design automation tools

Job description

Skyworks Solutions, Inc. in Irvine is seeking a Winter/Spring 2027 Co-op on the Filter Design team.

You will work with RF professionals to improve acoustic filters (SAW/BAW) and contribute to data-driven analysis and design automation. This on-site, six-month program invites PhD or Master’s students in engineering or related fields to apply mathematical algorithms, statistics, and machine learning to real-world filter design challenges, under mentorship.