AI Inference Core - Junior SDET, Release Integration Testing

Cerebras Systems

4d•Hybrid

About The Position

Cerebras Systems is seeking a Junior Software Development Engineer in Test (SDET) to join the Release Integration Testing (RIT) function within Release & Feature Qualification for AI Inference Core. This role is crucial for transforming integrated features into reliable production releases. The successful candidate will be responsible for writing software and automation, testing new model and platform capabilities, investigating failures in a complex AI system, and maintaining stable master and release branches. This is an ideal opportunity for an early-career engineer with a passion for coding, debugging, understanding system interdependencies, and rapid learning, with experience gained through internships, research, academic projects, or open-source contributions. The RIT team acts as a bridge between feature and release qualification, focusing on integration strategy, readiness evidence, cross-stack validation, and initial rollout triage for inference-core changes.

Requirements

Strong software-engineering fundamentals and programming ability in Python, Go, or a similar language.
Experience—through internships, research, academic projects, open source, personal projects, or professional work—building, testing, or debugging software.
Basic understanding of data structures, algorithms, operating systems, networking, or distributed-systems concepts.
Curiosity about how complex systems behave across component boundaries.
Ability to break down problems, form hypotheses, gather evidence, and learn from unexpected results.
Willingness to read unfamiliar code, learn new layers of the stack, and take ownership beyond a narrowly defined task.
Clear communication, collaboration, persistence, learning velocity, and comfort working through ambiguity with guidance.

Nice To Haves

Coursework or project experience in testing, distributed systems, operating systems, compilers, computer architecture, AI systems, or infrastructure.
Experience building automated tests, test frameworks, CI workflows, developer tools, or data-analysis scripts.
Exposure to software/hardware co-design, hardware accelerators, low-level systems, or performance debugging.
Familiarity with AI infrastructure, model deployment, LLMs, multimodal workloads, containers, or cloud environments.
Experience using logs, metrics, debuggers, profilers, or observability tools to investigate failures.
Internship, startup, research-lab, robotics, systems, or other fast-moving hands-on experience.
Demonstrated zero-to-one initiative through a substantial project, tool, experiment, or open-source contribution.

Responsibilities

Engage with selected inference-core features before qualification completes to understand dependencies, interaction risks, and the required integration scenarios.
Develop, run, and maintain automated tests for models, features, system behavior, integration, regression, and releases across the AI stack.
Collect unit, simulation, benchmark, feature-test, and integration evidence; document gaps; execute cross-stack E2E workflows; and promote durable scenarios into release regression.
Help maintain master and release-branch stability by triaging regression and rollout failures, escalating with clear evidence, identifying owners, validating fixes, and verifying closure.
Write Python, Go, or similar code for test automation, diagnostics, testbeds, data analysis, dashboards, qualification workflows, and release pipelines.
Collaborate with Integration, Core Infra, feature teams, and release owners to reproduce issues, route missing coverage to the correct layer, and support coordinated rollout across multiple product and release projects.
Document test intent and findings, grow toward independent ownership of a test domain, and between active engagements improve automation efficiency, metrics, probes, diagnostics, and roadmap test plans.