Cerebras

1 day ago

AI Inference Core - SDET Technical Lead, Release Integration Testing

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 27 minutes agoStatus: Live

Job Summary

Establish and lead Release Integration Testing (RIT) for AI Inference Core, defining quality strategy across the feature-to-release cycle. Own the inference-path readiness gate, review evidence across unit/simulation/benchmark/feature/integration tests, and approve integration readiness. Drive cross-stack E2E validation across the cloud-to-wafer stack, improve master/release-branch stability with health metrics and dashboards, and lead regression/rollout triage while mentoring engineers and building test automation.

Location: Sunnyvale, Toronto

Workplace: Hybrid

Employment Type: Full time

Job Function: QA, Test & Release Engineering

Key Responsibilities

•Define the RIT strategy, engagement criteria, ownership boundaries, entry/exit criteria, coverage expectations, and escalation thresholds for AI Inference Core.
•Engage early on high-risk inference changes and manage dependencies/interaction risks across runtime, host, device programming, memory, scheduling, model execution, infrastructure, and hardware.
•Own the inference-path readiness gate by reviewing evidence across unit, simulation, benchmark, feature-test, and integration, documenting gaps, and approving integration readiness.
•Lead integrated inference E2E validation across features and the cloud-to-wafer stack, promoting durable tests and adding risk-based scenarios to release regression.
•Improve master and release-branch stability using health metrics, failure classification, release-quality reporting, dashboards, qualification workflows, and release pipelines, and lead first-pass regression/rollout triage.

Key Requirements

•Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.
•Demonstrated technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex software integration.
•Experience designing automation and test architecture for distributed, systems-level, infrastructure, or AI software.
•Proven ability to break down ambiguous cross-stack failures, form hypotheses, gather evidence, and drive issues to resolution.
•Strong understanding of risk-based testing, release readiness, regression strategy, failure analysis, and quality metrics.

Experience:AI infrastructureDistributed systemsRelease engineeringTest automation

Skills:Technical leadershipProblem-solvingCommunicationSound judgmentCross-team alignment

Tech Stack:PythonC++GoCI/CDContainersLLMsBenchmarksDashboardsRelease pipelines

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 day ago

AI Inference Core - SDET Technical Lead, Release Integration Testing

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 27 minutes agoStatus: Live

Job Summary

Location: Sunnyvale, Toronto

Workplace: Hybrid

Employment Type: Full time

Job Function: QA, Test & Release Engineering

Key Responsibilities

•Define the RIT strategy, engagement criteria, ownership boundaries, entry/exit criteria, coverage expectations, and escalation thresholds for AI Inference Core.
•Engage early on high-risk inference changes and manage dependencies/interaction risks across runtime, host, device programming, memory, scheduling, model execution, infrastructure, and hardware.
•Own the inference-path readiness gate by reviewing evidence across unit, simulation, benchmark, feature-test, and integration, documenting gaps, and approving integration readiness.
•Lead integrated inference E2E validation across features and the cloud-to-wafer stack, promoting durable tests and adding risk-based scenarios to release regression.
•Improve master and release-branch stability using health metrics, failure classification, release-quality reporting, dashboards, qualification workflows, and release pipelines, and lead first-pass regression/rollout triage.

Key Requirements

•Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.
•Demonstrated technical leadership in software quality, test infrastructure, systems validation, release engineering, or complex software integration.
•Experience designing automation and test architecture for distributed, systems-level, infrastructure, or AI software.
•Proven ability to break down ambiguous cross-stack failures, form hypotheses, gather evidence, and drive issues to resolution.
•Strong understanding of risk-based testing, release readiness, regression strategy, failure analysis, and quality metrics.

Experience:AI infrastructureDistributed systemsRelease engineeringTest automation

Skills:Technical leadershipProblem-solvingCommunicationSound judgmentCross-team alignment

Tech Stack:PythonC++GoCI/CDContainersLLMsBenchmarksDashboardsRelease pipelines

Company Brief

Cerebras

Industry: Hardware Devices

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

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn