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.
As Characterization Lead, you will own performance characterization of Zinal retimer silicon and the Randa Active Electrical Cable (AEC) channel.
This is a Principal / Senior Staff individual contributor role with hands-on technical leadership.
Your measurements will establish datasheet limits, channel classes and guard-bands for validation, manufacturing and customer specifications.
Based primarily in Lausanne, you will work with silicon, signal integrity and validation teams, including channel characterization partners in Taiwan.
Responsabilities· Lead silicon and channel characterization from measurement planning and bench setup through analysis, limit derivation and documented hand-off to validation.
· Characterize TX/RX SerDes performance across process, voltage and temperature: swing, jitter, sensitivity, equalization, adaptation, CDR lock, BER bathtubs and shmoos.
· Own channel measurements to at least 50 GHz, including de-embedding, insertion/return loss, mixed-mode S-parameters and common-mode and mode-conversion behavior.
· Establish reference-paddle baselines and channel classes by gauge, reach and frequency; correlate HTDR-derived metrics with calibrated VNA measurements.
· Derive datasheet limits and guard-bands from measured distributions, accounting for uncertainty, sample coverage and aging; maintain traceable datasets and limit revisions.
· Assess carrier-loading and forwarded-clock.