Lenovo
AI Infra Staff Researcher
Morrisville, North Carolina · Staff · Full-time · Posted Aug 10, 2026
- Experience
- Three 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
Conduct applied research and develop production-quality software for efficient, reliable AI compute and data infrastructure, including cross-layer optimization of hybrid AI systems.
What you'll do
- Research and build AI infrastructure software, diagnostics, data pipelines, and resilience mechanisms.
- Profile AI workloads and diagnose performance or reliability issues across hardware, systems, and AI frameworks.
- Apply machine learning and other analytical methods to infrastructure optimization, forecasting, and root-cause analysis; help transition research into products.
What they ask for
- Bachelor's degree in a related field or equivalent practical experience.
- Three or more years of relevant experience.
- Strong programming skills in a listed or comparable language; ability to design, implement, test, debug, profile, and optimize reliable software systems.
- Experience in profiling, telemetry analytics, observability, performance diagnosis, or failure analysis, plus technical expertise in at least two listed areas.
Nice to have
- Experience with listed AI, data, infrastructure, or accelerator technologies such as PyTorch, CUDA, Spark, or Kubernetes.
- Experience with hybrid AI infrastructure, production delivery of research or advanced software, or publications, patents, open-source contributions, or product impact.
Tools
Python, C++, Java, Go, Rust, Scala, PyTorch, TensorFlow
AI focus
Applied research and development for AI compute and data infrastructure, including machine learning for workload modeling, performance prediction, resource optimization, failure prediction, and operational decisions.
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