SerDes Architecture and Modeling Engineer, CH

• Implement, document, and maintain software for system-level modelling of serial communication links in MATLAB, Python, and C++

• Work closely with system architects in order to budget the link and define block-level specs of the transceiver

• Work closely with analog, digital, and verification teams in order to support the design and verification process

Do you have experience in Python?, Do you have a Bachelor's degree?, * Good knowledge of control theory and digital algorithms

• Demonstrated skills in implementing signal-processing algorithms

• Understanding of the building blocks of a digital communication link and factors impacting the link performance (Familiarity with SerDes link components and clock recovery circuits is a plus)

• Proficient in at least one of the following programming languages C++, MALTAB, or Python/NumPy.

• Familiar with git version-control system and fundamentals of software engineering (unit-testing, profiling, …)

• Familiar with analog circuit simulators (SPICE/SPECTRE)

• Familiar with principles of signal integrity

• Strong communication and presentation skills

Preferred Experience:

• 5+ years of experience in semiconductor, telecommunications, or mathematical/scientific software industry

• Experience with system-level simulation of digital communication systems (experience in SerDes links is a plus)

• Experience working with geographically dispersed teams

Education

• Bachelor of Engineering in Electronics and Electrical Engineering, Communication Systems, or Computer Science (equivalent or higher) with strong background in Signal Processing and good understanding of Circuits Theory

If this is the role you have been looking for and you want to be part of a growing Company, with an exciting future then we would really love to hear from you. Together We Kandou It !

At Kandou, we are redefining the economics of AI infrastructure. Our mission is to democratise AI by significantly reducing the Total Cost of Ownership (TCO) of hardware systems - a critical barrier to scalable adoption. Our proprietary MIMO-over-copper technology powers a high-performance, chiplet-based AI memory fabric that is both scalable and energy-efficient. Unlike traditional interconnects, our solution reduces power consumption significantly while preserving high bandwidth and ultra-low latency - unlocking unprecedented efficiency for AI training and inference at scale. Kandou's architecture is not just an incremental improvement - it's a foundational shift in how AI hardware is built for the future.