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Optical Network Engineer

MatX
CompanyMatX
CategoryEngineering
LocationMountain View
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted15 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (greenhouse)
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Description
What MatX Is Building MatX's mission is to make the world’s best AI models run as efficiently as allowed by physics, bringing the world years ahead in AI quality and availability. About the Role This is a senior-level, highly specialized engineering role focused on the design, qualification, and productization of next-generation optical interconnect technologies for AI scale-up and scale-out networks. The engineer owns the full lifecycle — from component characterization and link budget analysis to system-level bring-up and data center deployment — across the evolving spectrum of optical integration approaches: pluggables, NPO, and CPO . What You'll Do Technology Evaluation & Qualification Validate and productize high-speed copper and optical connectivity solutions for AI accelerator systems; own vendor due diligence and onboarding for new 1.6T products including AEC and pluggable optical transceivers.   Characterize and qualify optical modules across the integration spectrum — DSP Optics, LRO, LPO, NPO, and CPO — for 800G and 1.6T deployment in scale-up AI fabrics Perform link budget analysis and evaluate performance metrics including TDECQ, OMA, stressed receiver sensitivity, and associated diagnostics. Component & System Engineering Develop expertise in transceiver components including CW lasers, SiPh PICs, EML, DSP, passive subassemblies, their failure modes, and characterization methodologies.   Evaluate silicon photonics (SiPh) transceivers, VCSEL-based MMF links, and EML-based SMF solutions for scale-up fabric topologies Apply knowledge of thermal, mechanical, power, and signal integrity constraints in dense hardware environments. Scale-Up Network Architecture Define optical interconnect strategy for AI cluster topologies — rail-optimized, torus, dragonfly, and Clos — at XPU counts from 10K to 1M+ Model and optimize end-to-end link budgets for 1.6T (200G/lane PAM4) across fiber types: SMF, MMF, MCF Engage with the transition from 1.6T to 3.2T (400G/lane) roadmaps and new form factors emerging with LPO and CPO. Supply Chain & Vendor Management Develop familiarity with subcomponent supply chains and global manufacturers, ODMs, and CMs. Manage technical relationships with optical module vendors (Coherent, II-VI/Coherent, Lumentum, Innolight, HG Genuine, Eoptolink) and silicon photonics suppliers Drive NPI (New Product Introduction) qualification plans, yield improvement, and reliability testing with manufacturing partners What We're Looking For Experience & Education BS/MS/PhD in Electrical Engineering, Optical Engineering, Physics, or Photonics 7–12+ years in optical interconnect engineering, with at least 3 years focused on data center or AI fabric applications Hands-on experience qualifying 400G, 800G, or 1.6T optical modules in production environments Deep knowledge of PAM4 signal theory, SerDes architecture, and optical link physics at 200G per lane Proficiency in optical test equipment: BERT, OTDR, optical spectrum analyzers, sampling oscilloscopes (e.g., Keysight 86100), optical power meters, TDECQ testers Experience with OIF-CEI, IEEE 802.3dj electrical and optical compliance specs In-depth expertise in debugging and troubleshooting hardware; experience in the product development lifecycle. Understanding of fiber plant requirements: MPO/MTP connector, fiber cleanliness, insertion loss, PMD, and bend radius for high-density AI cluster cabling Experience with link budget modeling tools (MATLAB, Python-based photonic simulation, GNPY) Ability to collaborate with switch ASIC teams (SerDes architects), PCB/signal integrity engineers, thermal/mechanical engineers, and NOS/software teams Strong technical documentation and vendor communication skills Bonus Points Background in AI accelerator or GPU system validationFamiliarity with JEDEC or PCIe compliance testing method
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