OG
Performance Modeling Architect
Accepting applicationsOho Group · San Francisco Bay Area
Full-Time Mid_senior AIC++Python
Posted
2d ago
Category
Verification
Experience
Mid_senior
Country
United States
Principal Performance Modeling Architect — AI Systems
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.
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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.
Show more Show less