Senior AI Compute & Data Infrastructure Researcher

Lenovo

North Carolina

Hybrid

USD 140,000 - 190,000

Full time

14 days+

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Job summary

Lenovo in Morrisville, NC, seeks a Staff Researcher in AI Compute and Data Infrastructure to conduct applied research and hands-on development for resilient Hybrid AI systems. The role spans AI algorithms, systems, data infrastructure, and cross‑layer optimization across GPUs, CPUs, memory, and storage.

The successful candidate will own substantial workstreams, build production‑quality software, characterize workloads, diagnose infrastructure issues, and collaborate across hardware and product

Qualifications

  • Bachelor's degree or equivalent in CS/EE/AI or related field
  • 3+ years in AI compute, data infrastructure, ML systems, distributed data platforms, or performance engineering
  • Strong programming in Python, C++, Java, Go, Rust or Scala

Responsibilities

  • Research and develop AI compute and data infrastructure technologies across GPUs, CPUs, memory, storage, and networks.
  • Design production‑quality software, system components, services, APIs, and data pipelines.
  • Characterize AI training and inference workloads using profiling, telemetry, logs, and performance counters.
  • Diagnose bottlenecks across GPUs, accelerators, CPUs, memory hierarchies, and software stacks.
  • Develop co‑optimization strategies for hardware/software workloads and resource management.
  • Build fault tolerance, checkpointing, recovery, and automated remediation.

Skills

Python
C++
Java
Go
Rust

Education

Bachelor's degree in CS/CE/AI or related field

Tools

CUDA
Kubernetes
PyTorch
TensorFlow
Spark

Job description

Lenovo in Morrisville, NC, seeks a Staff Researcher in AI Compute and Data Infrastructure to conduct applied research and hands-on development for resilient Hybrid AI systems. The role spans AI algorithms, systems, data infrastructure, and cross‑layer optimization across GPUs, CPUs, memory, and storage.

The successful candidate will own substantial workstreams, build production‑quality software, characterize workloads, diagnose infrastructure issues, and collaborate across hardware and product

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