Lenovo
AI Infra Advisory Researcher
Morrisville, North Carolina · Full-time · Posted Aug 10, 2026
- Experience
- Five or more years of relevant experience.
- Education
- Bachelor's degree in computer science, computer engineering, artificial intelligence, electrical engineering, applied mathematics, or a related field, or equivalent practical experience.
- Visa sponsorship
- Must be a US citizen or US national; US permanent residents and candidates requiring sponsorship cannot be considered.
About the job
Provides technical leadership for researching, architecting, and developing high-performance, resilient AI compute and data infrastructure, from hardware and distributed systems through production AI workloads.
What you'll do
- Lead research and architecture initiatives for AI compute, data infrastructure, and distributed AI systems.
- Design and optimize end-to-end infrastructure, including GPU and hardware/software optimization, data pipelines, observability, and reliability.
- Apply machine learning, time-series methods, causal inference, and knowledge graphs to infrastructure optimization and operations; guide teams and transition research into products.
What they ask for
- Bachelor's degree in a related field or equivalent practical experience.
- Five or more years of relevant experience.
- Leadership of technically complex research, architecture, or system development initiatives; strong hands-on programming and system architecture capabilities.
- Deep expertise in at least three listed areas, plus a record of delivering advanced software, infrastructure, or research technologies into products or production.
Nice to have
- Experience architecting enterprise-scale cloud, edge, on-premises, or hybrid AI infrastructure.
- Experience with listed AI, compute, data, or infrastructure technologies; MLOps, observability, distributed computing, data lakehouse, or cloud-native systems; publications, patents, open source, or commercial product impact.
Tools
PyTorch, TensorFlow, JAX, CUDA, ROCm, Spark, Flink, Ray
AI focus
Research and development of AI compute and data infrastructure; applying machine learning and deep learning to infrastructure control, forecasting, optimization, failure prediction, and operational intelligence.
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