AI System Performance Engineer
Intel Corporation (company site, opens in a new tab)1+ yrsBengaluruOn-siteDirect career pageEst. 12–22 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop and maintain analytical performance models and simulators for AI training and inference systems focused on GPU and Intel architectures.
- Identify architectural bottlenecks through modeling of multi-GPU deployment, parallelism, communication, and hardware configurations to recommend optimized system designs.
- Perform what-if analyses by varying GPU core count, memory/cache parameters, interconnect and deployment options, delivering actionable architecture optimization recommendations.
Minimum Requirements
- BTech or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field.
- 1+ years experience in AI workload and GPU architecture modeling/simulation or a similar technical field.
- Strong proficiency in Python capable of building modular analytical models and simulation frameworks.
- In-depth understanding of computer architecture including GPU/CPU cores, memory hierarchy, and LLM AI workloads (e.g. Transformer, MoE, Attention).
Ideal Candidate Profile
- Experience working with multi-GPU distributed training and inference parallelism strategies, including understanding of communication patterns at scale.
- Familiarity with LLM inference and training internals, kernel operations, batching, KV cache, and quantization.
- Able to quickly absorb new architectures, tools, workloads, and work in analytical simulation environments focusing on performance and architectural bottleneck identification.