Principal Architect, Performance Analysis and Modeling

d-MatrixSanta Clara, CA
$175,000 - $285,000Hybrid

About The Position

At d-Matrix, we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration. We value humility and believe in direct communication. Our team is inclusive, and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution. Ready to come find your playground? Together, we can help shape the endless possibilities of AI. Working onsite at our Santa Clara, CA, headquarters 3 days per week hybrid. Will consider remote in the United States. Will consider remote in the United States. The role: Principal Software Engineer, Performance Analysis and Modeling d-Matrix is looking for a computer engineer to help analyze and model performance across the hardware/software boundary of our AI inference accelerators. This role focuses on emerging hardware technologies (DIMC, D2D, 3D-DRAM) and emerging workloads (generative inference, multi-modal LLMs) — building the analytical models and simulation tools that let the architecture team project performance on current and future d-Matrix silicon. You'll work closely with Hardware Design, Compiler, Inference Server, and Kernels teams, translating workload analysis into concrete modeling inputs and surfacing HW/SW improvement opportunities. This is a hands-on technical contributor role within the broader architecture organization.

Requirements

  • BSEE with 6+ years of industry experience, or MSEE with 4+ years of industry experience.
  • Working knowledge of computer architecture, HW/SW co-design, performance modeling, and ML fundamentals (particularly DNNs).
  • Programming fluency in C/C++ or Python.
  • Experience building or working with analytical performance models or architecture simulators.
  • Self-motivated and collaborative, comfortable working across hardware and software teams.

Nice To Haves

  • Experience optimizing AI/ML workloads on accelerator technologies
  • Research and investigation in AI/ML architecture/microarchitecture

Responsibilities

  • Analyze emerging ML workloads, multi-modal LLMs, CoT reasoning models, and video/audio generation to identify performance-relevant properties.
  • Build and maintain analytical performance models that project behavior on current and future d-Matrix hardware generations.
  • Develop and extend architecture simulators to support performance analysis of proposed HW/SW features.
  • Partner with hardware design, compiler, inference server, kernel, and product teams to validate modeling assumptions and surface downstream implications.
  • Track relevant ML architecture and algorithms research and incorporate findings into modeling work.
  • Propose targeted HW/SW feature improvements based on modeling results and workload analysis.
  • Document modeling methodology and findings for reuse across the architecture team.
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