Cerebras

4 months ago

ML Performance Benchmarking Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Build and scale software capabilities that measure, analyze, and optimize AI inference performance on Cerebras’ Wafer-Scale Engine. Own end-to-end observability telemetry, benchmarking automation, and performance analysis to identify bottlenecks and drive actionable improvements. Partner with Core Platform teams to define testing methodologies that validate inference features for peak throughput and low latency—from prototyping through production deployment.

Location: Toronto

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Design and implement end-to-end telemetry systems to provide deep observability into inference performance.
•Architect, build, and scale benchmarking infrastructure that generates, analyzes, and visualizes performance data.
•Investigate system behavior to dissect performance bottlenecks and deliver actionable insights for product and feature decisions.
•Partner with Core Platform teams to define rigorous testing methodologies validating inference features for peak performance.
•Support performance improvements across the lifecycle, from early prototyping to production deployment.

Key Requirements

•Bachelor’s or Master’s degree in Computer Engineering, Systems Engineering, or a related field.
•Proficiency in Python and/or C++ programming.
•Proven experience building and scaling automated infrastructure.
•Strong background in throughput and performance optimization for complex, large-scale systems.
•Excellent problem-solving skills and an analytical mindset, with the ability to dive deep into new domains.

Experience:AI workloadsAI-native startupsInference performance

Education:Bachelor's in Computer Engineering or Systems Engineering

Skills:Problem-solvingAnalytical mindsetCollaborationAdaptabilityFast-paced execution

Tech Stack:PythonC++TelemetryAutomationInference performanceScheduling

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

4 months ago

ML Performance Benchmarking Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Toronto

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Design and implement end-to-end telemetry systems to provide deep observability into inference performance.
•Architect, build, and scale benchmarking infrastructure that generates, analyzes, and visualizes performance data.
•Investigate system behavior to dissect performance bottlenecks and deliver actionable insights for product and feature decisions.
•Partner with Core Platform teams to define rigorous testing methodologies validating inference features for peak performance.
•Support performance improvements across the lifecycle, from early prototyping to production deployment.

Key Requirements

•Bachelor’s or Master’s degree in Computer Engineering, Systems Engineering, or a related field.
•Proficiency in Python and/or C++ programming.
•Proven experience building and scaling automated infrastructure.
•Strong background in throughput and performance optimization for complex, large-scale systems.
•Excellent problem-solving skills and an analytical mindset, with the ability to dive deep into new domains.

Experience:AI workloadsAI-native startupsInference performance

Education:Bachelor's in Computer Engineering or Systems Engineering

Skills:Problem-solvingAnalytical mindsetCollaborationAdaptabilityFast-paced execution

Tech Stack:PythonC++TelemetryAutomationInference performanceScheduling

Company Brief

Cerebras

Industry: Hardware Devices

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

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn