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Product Engineering Internship, Simulation and Verification (Summer 2026)

Cadence Design Systems
Posted 13 days ago, valid for a month
Location

Burlington, MA 01805, US

Salary

Competitive

Contract type

Full Time

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Sonic Summary

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  • Cadence is seeking a Product Engineering Intern for the Summer 2026 semester, located in their Burlington office.
  • The intern will work on simulation and verification-validation testing of high-speed digital systems, including PCB simulation and impedance profiling.
  • Candidates must be currently enrolled in a Master's program in Electrical Engineering or a related field, with relevant coursework or experience in electromagnetics and signal processing.
  • Experience with signal integrity analysis tools such as Cadence Sigrity, ADS, or HFSS is required, and familiarity with machine learning is a plus.
  • The position requires a commitment of 40 hours per week on-site, and while the salary is not specified, internships typically offer competitive compensation.

At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.

Product Engineering Internship, Simulation and Verification (Summer 2026)

This PE Internship will be based out of our Burlington office during the Summer Semester.

Responsibilities:

  • As a Product Engineering intern, you will get the opportunity to work on the simulation and verification-validation testing of high-speed digital systems.
  • Simulate PCBs and packages in commercial 2.5D electromagnetics simulators to extract models and subsequently, impedance profiles; perform time domain analysis
  • Provide feedback to developers on simulation tool usage

Requirements:

  • Currently enrolled as student pursuing MSEE or equivalent
  • Experience or course work in electromagnetics, optimization, signal processing and system analysis, and channel theory or associated courses.
  • Experience using signal integrity analysis and extraction tools (Cadence Sigrity, ADS, HFSS)
  • Interest, or have experience in machine learning is a plus.
  • Must be available to work onsite in Burlington office 40 hours a week. This role is not remote.

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