Principal AI Systems Performance Engineer
Micron Technology, Inc. (company site, opens in a new tab)10+ yrsHyderabadOn-siteDirect career pageEst. 45–75 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Lead controlled experiments on current and pre-production CPU-GPU systems to identify how memory, storage, interconnects, power and thermal limits affect AI workload performance.
- Analyze AI workloads from GPU memory through system memory, CXL and storage, at node and cluster scale; evaluate data placement, migration, prefetching, compression and tiering.
- Convert measurements and performance models into future system requirements, engineering and product recommendations, and guidance for customer-facing teams.
Minimum Requirements
- Work Experience Required: Bachelor’s degree plus at least 10 years of experience; master’s degree plus at least 5 years; or a Ph.D. with demonstrated experience in a related field.
- Hands-on profiling and benchmarking of multi-GPU AI systems in 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 and Python, plus at least one of C, C++, CUDA or Triton.
Ideal Candidate Profile
- Has experience evaluating end-to-end AI system performance, including memory, storage, interconnects and data movement across node and cluster scales.
- Can turn controlled measurements, traces or models into forward-looking system requirements and practical recommendations for engineering, product and customer teams.
- Has relevant depth in memory tiering, KV-cache management, disaggregated infrastructure or performance modeling; these are preferred signals, not stated minimum requirements.