Research Manager, AI Infrastructure

Lenovo•San Jose, CA

15h•$202,800 - $310,960•Hybrid

About The Position

Lenovo Intelligent Computing Lab is seeking a technically credible, strategically minded researcher and leader to join its research group in AI computing infrastructure technology. The role works with researchers to translate systems research into product and business impact, and owns the roadmap connecting emerging AI infrastructure technologies to Lenovo’s Hybrid AI strategy. It balances long-term research priorities with near-term product deliverables. This is a hybrid role in Palo Alto, with onsite work required three days per week. Applicants must be US citizens or US nationals; permanent residents and candidates requiring sponsorship cannot be considered.

Requirements

Advanced degree (PhD or MS) in computer science, computer engineering, or a related discipline.
At least 8 years of experience in systems, architecture, or AI infrastructure R&D, including at least 3 years leading research or advanced development teams.
Deep technical grounding in at least two of the following: AI accelerators and intelligent computing; datacenter networking; storage systems; memory hierarchy or KV cache optimization; energy-efficient systems design; distributed training or inference stacks.
Demonstrated record of translating research into shipped products or production infrastructure.
Must be a US citizen or US national; US permanent residents and candidates requiring sponsorship cannot be considered.

Nice To Haves

Publications at top-tier systems, architecture, or machine learning venues, and/or a substantial patent portfolio.
Direct experience with LLM serving optimization, such as KV cache management, speculative decoding, disaggregated prefill/decode, or quantization-aware serving.
Experience with agentic AI systems, including multi-agent orchestration, tool-use pipelines, long-context inference, 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, such as carbon-aware scheduling and performance-per-watt optimization.

Responsibilities

Define and identify high-leverage research bets in AI computing infrastructure, prioritizing them 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, inference, and serving.
Partner with product, engineering, and business development teams to transition research into Enterprise AI and Personal AI product lines.
Own the roadmap connecting emerging AI infrastructure technologies to Lenovo’s Hybrid AI strategy, balancing long-horizon research with near-term product deliverables.