Research Manager, AI Infrastructure

Lenovo • Morrisville, NC

6d • Hybrid

About The Position

Lenovo Intelligent Computing Lab (ICI) is seeking a technically credible, strategically minded researcher/leader to join their world-class research group in AI computing infrastructure technology. The team is a global group of highly qualified researchers and engineers advancing the frontier of AI infrastructure and agentic AI acceleration to power Lenovo's next-generation Hybrid AI strategies. They bring 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.

Requirements

• 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.
• Must be a US citizen or US national; US permanent residents or candidates requiring sponsorship cannot be considered.

Nice To Haves

• 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).

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior