Staff Performance Modeling Engineer, AI Hardware Systems

Netpreme; Boston (MA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

Health coverage

Dental coverage

Vision coverage

401(k) match

Life insurance

Disability insurance

AD&D insurance

PTO 20 days

Company holidays

Lunch stipend

Office parking

EV charging

Visa sponsorship

Relocation assistance

Equity grant

Job summary

Netpreme seeks a Member of Technical Staff to develop functional and performance models for a scale-up memory expansion device for AI accelerators. You will work with the silicon architecture team to explore tradeoffs, validate assumptions, and identify bottlenecks early in development.

This onsite role offers collaboration with silicon architects and workload owners, opportunities to reason from first principles across abstraction layers, and to influence design space as hardware and software

Qualifications

• 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.

Responsibilities

• Build and maintain system-level (e.g., rack-scale) and chip-level performance models for high-bandwidth data movement between devices operating in the scale-up domain.
• Model workloads from software memory access patterns through data distribution in the network and all the way down to on-device memory channels.
• Work day-to-day with silicon architects, system designers, and workload owners to align performance expectations and constraints.
• Identify performance bottlenecks, scaling limits, and sensitivity points across compute, memory, and interconnects in end-to-end workload settings.
• Clearly communicate modeling assumptions, limitations, and conclusions to both technical and non-specialist stakeholders.

Skills

Performance modeling

Cross-layer reasoning

Bottleneck identification

Education

Bachelor’s or Master’s degree in Electrical Engineering or Computer Engineering

Tools

CUDA VMM

NVLink

NoC

Job description

Netpreme seeks a Member of Technical Staff to develop functional and performance models for a scale-up memory expansion device for AI accelerators. You will work with the silicon architecture team to explore tradeoffs, validate assumptions, and identify bottlenecks early in development.

This onsite role offers collaboration with silicon architects and workload owners, opportunities to reason from first principles across abstraction layers, and to influence design space as hardware and software