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Salary
≈ $130k – $251k per year (Estimated)
Location
Hybrid (Morrisville, United States)
Seniority
Senior · 8+ years exp

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Oct 26, 2026. Lenovo scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Lenovo Group Limited is a global technology enterprise specializing in personal computing, smart devices, data center infrastructure, and enterprise IT services. Headquartered in Beijing, China, and Morrisville, North Carolina, United States - with its registered office in Hong Kong - the publicly traded corporation operates across three primary business divisions: the Intelligent Devices Group (IDG), the Infrastructure Solutions Group (ISG), and the Solutions and Services Group (SSG). Through an extensive product and services portfolio encompassing ThinkPad and IdeaPad personal computers, Motorola smartphones, ThinkSystem enterprise servers, edge computing hardware, and hybrid cloud solutions, the enterprise provides hardware, software, and managed IT services to commercial clients, public institutions, and retail consumers across more than 180 markets worldwide.

*Please Note* This is a hybrid role in Morrisville, NC. 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 Qualifications:

  • 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)

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.

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