Senior High-Speed System Link Modeling Engineer
Confirmed on the employer's own hiring board on Nov 10, 2026. First seen by Alion on Nov 9, 2026. Ranovus scores A on the Alion truth index.
Senior High-Speed System Link Modeling Engineer
Ottawa, ON, Canada | Full-Time | Ranovus
ABOUT RANOVUS
Ranovus is a fabless semiconductor company headquartered in Ottawa, Canada, developing next-generation co-packaged optics (CPO) solutions for AI and data center interconnects. Our Odin optical engine integrates a Quantum Dot Multi-Wavelength Laser, Photonic Integrated Circuit (PIC), and ASIC into a single co-packaged module -- delivering the performance and density required by hyperscale AI infrastructure.
ABOUT THE ROLE
The High-Speed System Modeling Engineer develops and runs end-to-end link simulations for the Ranovus Odin optical engine. Working alongside the system modeling team, you will build high-fidelity channel models, run IBIS-AMI simulations, and develop new modeling capabilities that keep pace with the product's evolving architecture. Your simulations directly inform architecture trade-offs, link budget allocation, and pass/fail thresholds for hardware bring-up.
KEY RESPONSIBILITIES
Develop and run high-speed link simulations for the Odin optical engine: end-to-end channel modeling from SerDes TX/RX to optical RX/TX.
Build and maintain IBIS-AMI models for SerDes transmitters and receivers; run compliance simulations against OIF CEI and IEEE 802.3 channel masks.
Perform link budget sensitivity analysis: quantify the impact of insertion loss, jitter, crosstalk, and equalization on BER margin.
Develop new modeling features and capabilities as the architecture evolves (new modulation formats, FEC schemes, equalization topologies).
Correlate simulation results against hardware measurements to validate model accuracy and identify gaps.
Support bring-up teams by predicting pass/fail outcomes for specific channel configurations before hardware is available.
Contribute to link performance documentation and TER-traceable pass/fail thresholds.
REQUIRED QUALIFICATIONS
MSc. or Ph.D. in Electrical Engineering or related field.
5+ years in high-speed link simulation for SerDes, optical transceivers, or CPO interconnects.
Hands-on experience with IBIS-AMI simulation flows and channel compliance tools.
Strong understanding of PAM4 link performance: equalization, jitter, BER, and channel loss budgets.
Proficiency in Python or MATLAB for simulation automation, data analysis, and result visualization.
Experience running channel simulations and interpreting eye diagrams, bathtub curves, and BER contours.
NICE TO HAVE
Experience with optical channel modeling (insertion loss, back-reflection, modal noise) in CPO or transceiver systems.
Familiarity with FEC (KP4, KR4) gain and BER floor modeling.
Background in statistical link analysis (SLA) or statistical eye modeling.
Knowledge of OIF CEI-112G or IEEE 802.3ck channel specifications.
What You'll Do
You will play a key role in advancing next-generation laser products from development through qualification. By combining hands-on characterization, automation development, reliability testing, and machine vision inspection, you will help establish the data, tools, and processes needed to bring high-performance laser products into production. Working closely with R&D, qualification and reliability teams, packaging suppliers, and external test providers, you will contribute directly to the successful commercialization of cutting-edge photonic technologies.
Ranovus is an equal opportunity employer and welcomes applicants from all backgrounds and lived experiences, including those from equity deserving and underrepresented communities. We are committed to an accessible recruitment process in accordance with the Accessibility for Ontarians with Disabilities Act.
We are committed to delivering a respectful and transparent candidate experience, with clear and timely communication at every stage of the process. Ranovus Inc. is committed to leveraging new technologies and working efficiently. As a result, artificial intelligence systems may be used to support elements of our hiring process. These tools are designed to enhance consistency and efficiency, not replace human judgment. All hiring decisions are made by people, guided by care, context, and fairness.
Thank you for your interest in joining Ranovus. We look forward to connecting with you.