Research Manager, AI Infrastructure

*Please Note* This is a hybrid role in Palo Alto. This candidate will be required to work onsite three days a week. This candidate MUST be a US citizen or US national; US permanent residents or candidates requiring sponsorship cannot be considered. Position Description: Lenovo Intelligent Computing Lab (ICI) is seeking a technically credible, strategically minded researcher/leader to join our world-class research group in AI computing infrastructure technology. Who are we at Lenovo ICI Lab? A global team of highly qualified researchers and engineers advancing the frontier of AI infrastructure and agentic AI acceleration to power Lenovo next-generation Hybrid AI strategies The team brings deep, hands-on expertise across intelligent computing technology, AI networking, sustainability, AI data storage, KV cache & data acceleration, and hardware/software co-optimization to enable full-stack efficiency for model training, fine-tuning, and serving The team has a dual mandate and a proven record on both fronts: shipping future-defining products for Enterprise AI and Personal AI, and publishing research at top-tier venues in systems, architecture, and machine learning The Role and Responsibilities Work with a group of talented and motivated researchers and translate breakthrough systems research into product and business impact. You will own the roadmap connecting emerging AI infrastructure technologies to the company's Hybrid AI strategy, balancing long-horizon research bets with near-term product deliverables. Define and identify high-leverage research bets in AI computing infrastructure, prioritizing against product and business impact Provide hands-on technical guidance on system architecture, performance, power efficiency, and co-optimization trade-offs for LLM training, fine-tuning, and inference/serving Partner with product, engineering, and business development to transition research into Enterprise AI and Personal AI product lines Required

Advanced degree (PhD/MS) in computer science, computer engineering, or related disciplines 8+ years in systems/architecture/AI infrastructure R&D, including 3+ years leading research or advanced development teams Deep technical grounding in at least two of: AI accelerators and intelligent computing; datacenter networking; storage systems; memory hierarchy/KV cache optimization; energy-efficient systems design; distributed training/inference stacks Demonstrated record of translating research into shipped products or production infrastructure Preferred Qualifications: Track record of publications at top-tier systems, architecture, or ML venues, and/or a substantial patent portfolio Direct experience with LLM serving optimization (e.g., KV cache management, speculative decoding, disaggregated prefill/decode, quantization-aware serving) Experience with agentic AI systems: multi-agent orchestration, tool-use pipelines, long-context and memory-augmented inference Familiarity with hybrid AI deployment models spanning cloud, edge, and on-device NPUs Experience with sustainability metrics and energy-aware system design (carbon-aware scheduling, perf/watt optimization)