Micron is a global leader in memory and storage, powering AI and compute-intensive applications from cloud to edge with innovative semiconductor solutions.
About the role
As a Principal AI Systems Performance Engineer, you will direct experiments on AI training, inference, and agentic workloads across complete server systems. You will pinpoint where bandwidth, capacity, latency, power, and data movement restrict performance—then convert your discoveries into product requirements and guidance for engineering, product, and customer teams. Your efforts will link current measurements with the demands of future AI infrastructure. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor’s degree with at least 10 years of experience , master’s degree with 5 or more years , or Ph.D. with demonstrated experience in a related field
- Hands-on experience profiling and benchmarking multi-GPU AI systems across single-node and multi-node environments
- Understanding of transformer workloads, memory behavior, distributed systems, and agentic AI infrastructure
- Experience with PyTorch, an AI serving platform, Python, and at least one of C, C++, CUDA, or Triton
- Ability to lead controlled experiments and communicate results to technical and business audiences
More about this role
Our vision is to transform how the world uses information to enrich life for all .
Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.
Micron’s Data Center Workload Engineering team studies how real AI workloads use compute, memory, interconnects, and storage. We turn system-level measurements into insights that help build future Micron DRAM (DDR and LPDDR), HBM, CXL, and storage products.
As a Principal AI Systems Performance Engineer, you will direct experiments on AI training, inference, and agentic workloads across complete server systems. You will pinpoint where bandwidth, capacity, latency, power, and data movement restrict performance—then convert your discoveries into product requirements and guidance for engineering, product, and customer teams. Your efforts will link current measurements with the demands of future AI infrastructure.
- Develop and perform controlled, representative AI experiments on current and pre-production CPU-GPU systems, evaluating memory and storage performance, power, and thermal...
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