Principal Architect, Performance Analysis and Modeling

🇺🇸 Santa Clara, CA
$2K - $3K Annual
Posted 2 months ago
Expires June 9, 2026

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.

The role: Principal Architect- Performance Analysis and Modeling

d-Matrix is seeking outstanding computer architects to help accelerate AI application performance at the intersection of both hardware and software, with particular focus on emerging hardware technologies (such as DIMC, D2D, 3D-DRAM etc.) and emerging workloads (such as generative inference etc.). Our acceleration philosophy cuts through the system ranging from efficient tensor cores, storage, and data movements along with co-design of dataflow, and collective communication techniques.

What you will do:

- As a member of the architecture team, you will analyze the latest ML workloads (multi-modal LLMs, CoT reasoning models, video/audio-generation)

- You will contribute Hardware and Software features that power the next generation of inference accelerators in datacenters.

- This role requires to keep up the latest research in ML Architecture and Algorithms, and collaborate with different partner teams including Product, Hardware design, Compiler, Inference Server, Kernels.

- Your day-to-day work will include (1) analyzing the properties of emerging machine learning algorithms and workloads and identifying functional, performance implications (2) Creating analytical models to project performance on current and future generations...

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