Netpreme builds the X-Mem™ Networked Memory Tier™, co-designed from silicon to tokens. Backed by E14 Fund.
About the role
We are seeking a Member of Technical Staff, Functional and Performance Modeling to develop functional and performance models for our scale-up network-attached memory expansion device for AI accelerators. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a closely related field
- 5–10+ years of experience in performance modeling for data movement devices: NICs, memory expansion cards (e.g. CXL), IPU/DPU, NoC
- Ability to reason across multiple abstraction layers, from architectural details to system-level performance behavior
More about this role
The biggest bottleneck in AI systems today is memory. Chips compute faster than they can be fed data—a problem known as the memory wall—and Netpreme is building the solution that allows AI memory to scale independently of AI compute. Our approach spans the full stack, from a proprietary memory management framework at the XPU kernel and OS levels to X-Mem™, the world’s first Memory Processing Unit (MPU) silicon. Founded by MIT researchers at the intersection of optical networking, ML systems, and GPU kernel optimization, we’re based in Cambridge, MA, and Santa Clara, CA. We’re looking for people who want to own hard problems end to end—and help shape the next generation of AI systems.
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We are seeking a Member of Technical Staff, Functional and Performance Modeling to develop functional and performance models for our scale-up network-attached memory expansion device for AI accelerators.
You’ll work as part of our silicon architecture team to perform functional and performance modeling. You should have experience exploring design tradeoffs, validating performance assumptions, and identifying bottlenecks early in the development cycle. This role is...
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