Performance Modeling Engineer

We’re working with a semiconductor company designing a new programmable compute architecture for demanding AI workloads. They’re looking for a senior performance-modeling engineer to create the tools that guide architectural decisions before hardware exists. Your work will determine where performance is gained or lost across compute, memory, interconnect and complete AI systems. What you’ll work on Build analytical and simulation-based performance models Model processors, accelerators, memory hierarchies and interconnects Analyze transformer inference across single-device and multi-accelerator systems Evaluate latency, throughput, utilization, energy and cost trade-offs Characterize workload behavior using traces and representative benchmarks Identify architectural bottlenecks and propose measurable improvements Partner with hardware, compiler, runtime and inference teams Correlate models against simulation, emulation or silicon as the platform matures What we’re looking for Strong Python and/or C++ development Experience building performance models Deep computer-architecture and microarchitecture knowledge Understanding of compute pipelines, memory systems and data movement Ability to convert model results into concrete architecture decisions Experience with GPUs, AI accelerators, LLM inference, cluster modelling, roofline analysis, NoCs or cost-per-token analysis would be especially relevant. This is an architecture-shaping role where performance models influence both the silicon and the software designed around it. #J-18808-Ljbffr