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Performance Modeling Engineer

DensityAI

Posted about 3 hours ago

About the role

Own the pre-silicon performance modeling and analysis that sets the architectural targets for our AI accelerator silicon. You'll characterize target ML workloads, build the analytical and roofline models that project performance onto proposed hardware, and turn that analysis into the PPA trade-off guidance the architecture, RTL, and compiler teams design against —well before first silicon.

What you'll do

  • Own pre-silicon performance modeling and analysis — workload characterization, roofline / analytical models, and what-if trade-off studies that guide microarchitecture decisions before RTL is committed
  • Translate target ML workloads (transformer training/inference, attention, GEMM/conv, collectives) into performance projections across compute, memory-bandwidth, and interconnect bottlenecks
  • Drive PPA (performance / power / area) trade-off analysis with architecture, RTL, and software/compiler teams — recommend where to spend area, bandwidth, and power for the most performance
  • Define and own the performance KPIs and the methodology for tracking them from architecture through silicon
  • Correlate model projections against RTL, emulation, and post-silicon data as it arrives, and feed the deltas back into the model to keep it predictive

What we're looking for

  • Strong computer-architecture fundamentals — memory hierarchy, compute/bandwidth roofline, dataflow, on-chip interconnect/NoC, and accelerator/GPU/TPU-class datapaths
  • Demonstrated performance modeling or analysis experience: analytical or simulation-based projection of real workloads onto hardware, where your results drove actual design decisions
  • Deep understanding of how ML workloads map to hardware GEMM/conv/attention, quantization, parallelism (data/tensor/pipeline), and collective communication
  • Fluency in Python (C++ a plus) for building models, analysis pipelines, and trace/data analysis at scale
  • 5+ years in performance architecture, modeling, or analysis for CPUs, GPUs, accelerators, or complex SoCs

Compensation

Final offers depend on level, location, and skills relevant to the role. Additional compensation: equity grant per company guidelines; medical / dental / vision; 401(k); standard PTO.

Visa Sponsorship

DensityAI sponsors qualified candidates for H-1B, O-1, TN, E-3, and other employment-based visas, and we welcome applicants on F-1 OPT and STEM-OPT. Work authorization is required at start; we provide immigration support to secure or transfer status.

Equal Opportunity

DensityAI is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religious creed, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age (40+), sexual orientation, military or veteran status, pregnancy, or any other status protected by law. We comply with the California CROWN Act and provide reasonable accommodations on request.

Full compensation packages are based on candidate experience and relevant certifications.

California pay range
$180,000$250,000 USD

Job details

Workplace

Office

Location

Mountain View, CA

Salary

180k - 250k USD

per year

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DensityAI

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Building the fastest inference solution for frontier models

Key Team Members

David Lam

David Lam

Susie Summers

Susie Summers

Srikanth Arekapudi

Srikanth Arekapudi

Manan Salvi

Manan Salvi

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