Cerebras

1 week ago

ASIC Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Design ASIC micro-architecture features from high-level architecture specifications for a large-scale AI chip platform. Own performance/power modeling, run PPA trade-offs, and extract efficiency insights. Profile workloads to find bottlenecks and benchmark competitive performance, while collaborating with software teams on end-to-end cluster modeling and identifying kernel-level hardware acceleration opportunities.

Location: Sunnyvale

Workplace: Onsite

Employment Type: Full time

Job Function: Hardware, Embedded & Systems Engineering

Seniority: Mid level

Key Responsibilities

•Translate high-level architecture specs into micro-architecture feature requirements.
•Bring up new features in the performance/power model.
•Perform comprehensive power-performance-area (PPA) trade-offs for new architectural features.
•Profile workloads to identify bottlenecks and assess competitive benchmarking performance.
•Collaborate with software teams on end-to-end application modeling at the cluster level and identify kernel-level hardware acceleration opportunities.

Key Requirements

•Masters/PhD in Electrical/Computer Engineering.
•10+ years of experience in performance analysis and modeling across GPUs, CPUs, or accelerator products.
•Strong background in computer architecture and high-level architectural trade-offs.
•Build new performance models from scratch in Python (or similar analytical environments).
•Exposure to micro-code (kernel) performance bottlenecks and optimization techniques.

Experience:10+ yearsAI hardwareAccelerators

Education:PhD / Doctorate in Electrical/Computer Engineering

Tech Stack:PythonGPUsCPUsMicro-codePPAPerformance/power modelingWorkload profilingML workload profilingModel network architecture

Company Brief

Cerebras

Designs and builds wafer-scale AI accelerators and systems for large-scale deep learning workloads, delivering specialized hardware and software to accelerate model training and inference for enterprises and research institutions.

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn

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Cerebras

1 week ago

ASIC Architect

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Sunnyvale

Workplace: Onsite

Employment Type: Full time

Job Function: Hardware, Embedded & Systems Engineering

Seniority: Mid level

Key Responsibilities

•Translate high-level architecture specs into micro-architecture feature requirements.
•Bring up new features in the performance/power model.
•Perform comprehensive power-performance-area (PPA) trade-offs for new architectural features.
•Profile workloads to identify bottlenecks and assess competitive benchmarking performance.
•Collaborate with software teams on end-to-end application modeling at the cluster level and identify kernel-level hardware acceleration opportunities.

Key Requirements

•Masters/PhD in Electrical/Computer Engineering.
•10+ years of experience in performance analysis and modeling across GPUs, CPUs, or accelerator products.
•Strong background in computer architecture and high-level architectural trade-offs.
•Build new performance models from scratch in Python (or similar analytical environments).
•Exposure to micro-code (kernel) performance bottlenecks and optimization techniques.

Experience:10+ yearsAI hardwareAccelerators

Education:PhD / Doctorate in Electrical/Computer Engineering

Tech Stack:PythonGPUsCPUsMicro-codePPAPerformance/power modelingWorkload profilingML workload profilingModel network architecture

Company Brief

Cerebras

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn