Retym builds DSP silicon for optical networking in AI data centers—the connectivity layer between compute nodes. The stack (SystemVerilog, Verilog, Synopsys, Cadence, TSMC, SerDes, HFSS) reveals deep analog-mixed-signal and physical-design maturity; projects span ADC/DAC development, RTL-to-GDS flow ramp, and system-level test frameworks for a coherent optical transceiver. Hiring is heavily senior engineering (33 of 39 roles) across three countries, suggesting a post-Series-A product-in-flight scaling phase—pain points confirm this: timing closure, complex IP integration, distributed-team coordination, and low-power constraints are all signature stress points of first-silicon bringup.
Notable leadership hires: System Director, Marketing Director
Retym is a semiconductor startup designing coherent DSP chips that address AI infrastructure bottlenecks. The company targets hyperscalers and module makers building next-generation optical data center interconnects, shipping a purpose-built DSP architecture that reduces latency and power consumption relative to general-purpose solutions. Founded in 2021 and headquartered in Cupertino, the team combines chip design, optical networking, and systems expertise. Active development spans multiple sites (Austin integration noted in projects), with product architecture covering ADC/DAC front-ends, RTL design, and test frameworks for silicon validation.
Retym uses SystemVerilog, Verilog, and UVM for design; Synopsys and Cadence for EDA; TSMC for process technology; and MATLAB, HFSS for signal integrity and analog simulation. Production code includes Embedded C, Python, and Bash for infrastructure and test automation.
Current projects include high-end ADC/DAC development for optical communication in advanced process nodes, RTL-to-GDS flow ramp, system-level test frameworks for coherent DSP, and next-generation optical transceiver development. The team is also integrating multi-site deliverables and establishing DFT strategy for the silicon.
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Retym, Inc's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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