Phononic Inc

• Define end-to-end thermal architecture strategies for GPU servers, optical interconnects, and CPO-based systems • Develop system-level approaches to balance performance, heat dissipation, reliability, and energy efficiency • Design and optimize solutions for: High-power GPUs and accelerators, Dense optical I/O (pluggable and co-packaged optics), Rack- and cluster-level thermal constraints • Optimize cooling strategies for high-density AI workloads and optical bandwidth scaling • Analyze and improve thermal resistance, junction temperatures, and cooling efficiency • Lead design and evaluation of advanced cooling approaches, including: Air cooling (high-performance heatsinks, airflow optimization), Liquid cooling (direct-to-chip, cold plates), Immersion cooling and emerging techniques • Architect thermal solutions for: High-speed optical transceivers (400G/800G/1.6T+), Co-packaged optics (CPO) integrated with switch or GPU ASICs • Collaborate with silicon photonics teams to co-design thermal-aware optical packaging architectures • Design GPU server platforms optimized for thermal efficiency, including: Multi-GPU configurations and interconnect density, Power delivery and cooling integration, Airflow and liquid loop design • Drive innovations in rack-level and data center-level cooling, including: High-density rack (>50–100kW) thermal strategies, Integration with facility cooling systems, Optimization for power usage effectiveness (PUE)

• Develop differentiated messaging for thermal control systems for AI products (e.g., GPUs, ASICs, AI accelerators, SoCs, CPO, pluggable transceivers) • Articulate value across performance, power efficiency, and thermal design considerations • Translate complex concepts such as optical transceiver laser thermal control, AI server and GPU cooling, rack density, cooling requirements, and energy efficiency into customer-impact narratives • Lead launches of silicon and AI platform solutions optimized for high-density, thermally constrained environments • Develop GTM strategies that highlight performance-per-watt, cooling efficiency, and infrastructure readiness • Partner with product and engineering teams on positioning tied to data center scalability and sustainability • Analyze trends across AI infrastructure, high-performance computing (HPC), and data center thermal management • Track competitive approaches to liquid cooling, immersion cooling, advanced air cooling, and energy-efficient architectures • Develop insights on how competitors address heat density, power consumption, and AI cluster scaling challenges • Equip sales teams with materials explaining thermal tradeoffs, rack-level constraints, and cooling requirements • Develop tools to communicate TCO, power usage effectiveness (PUE), and data center operational efficiency • Collaborate with ecosystem partners including data center operators, cloud providers, and cooling and infrastructure vendors (e.g., liquid cooling solutions) • Create content on AI infrastructure challenges, including power delivery, cooling, and scaling constraints • Publish whitepapers and technical briefs on AI workload-driven thermal demands, cooling technologies (liquid cooling, immersion, direct-to-chip), sustainable AI infrastructure, etc. • Represent the company in discussions on AI data center design and efficiency trends