Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs.
Cerebras' current customers include top model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, over 10 times faster than GPU-based hyperscale cloud inference services. This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
The Cloud Quality team is responsible for the confidence behind every production release shipped to Cerebras Inference Cloud.
We work closely with platform, infrastructure, ML systems, and product engineering teams to ensure that rapid iteration never comes at the expense of customer trust. Our environment spans distributed cloud systems, multi-region deployments, APIs, orchestration layers, and hardware-backed inference services.
We are scaling quickly. The systems are growing in complexity, traffic is increasing rapidly, and release velocity remains high. We need engineers who can build quality systems that scale with the business.
About The RoleWe are hiring a Software Development Engineer in Test to own the quality of our weekly cloud releases end to end and to build the test infrastructure that lets the team scale. This is a hands-on senior IC role for someone who treats quality as a first-class engineering problem - not a downstream gate.
You will drive every release from branch cut to sign-off, build scalable test infrastructure that grows with customer load, and push back when quality is at risk. You will operate effectively across timezones, async-first, with clear written communication.
This is a role for someone who self-drives. You will frequently work without complete product specifications, decide under ambiguity, and ask the right questions before code lands - not after.
Responsibilities- Release Quality Ownership: Drive weekly cloud release qualification end to end. Read every PR in the release branch first-hand; understand what changed; decide where the risk is; and design the qualification that exercises the actual risk. Be the final voice before a release ships.
- Test Infrastructure at Scale: Build and evolve the test infrastructure - functional, integration, performance, and fault for the Inference Cloud platform. Plan for 20x growth in coverage, environments, and traffic. Today's setup will not survive tomorrow's load; design for the next horizon.
- End-to-End System Understanding: Reason through the full stack — client SDK, API, gateway, inference software, driver, hardware. Know enough to debug from any layer and to test the right thing.
- Code Review with Intent: Read and review developer PRs with genuine understanding of what each change does and what its blast radius is. Test the change's actual impact, not its surface area.
- Automation Expansion: Increase automation coverage continuously. Fix flaky tests rather than tolerate them. Use AI tooling effectively to accelerate test creation, debugging, and analysis.
- Quality Discipline: Choose high-value tests over volume metrics. Drive the team's standards for what "tested" means and what "ready to ship" means.
- Cross-Team Operation: Work with platform, ML, infrastructure, and product teams across timezones. Influence quality outcomes without owning every team's roadmap.
- 5+ years of experience in quality engineering, test engineering, or a closely related role, with substantial individual contributor experience on large-scale distributed systems or cloud infrastructure.
- Deep cloud platform experience, preferably AWS - networking, compute orchestration, container platforms, and multi-region production services. You can reason about what is happening at the cloud layer when something fails.
- Track record of building scalable test infrastructure - frameworks, harnesses, environments, and automation that scale with the system under test rather than fighting it.
- Strong systems debugging and reasoning. You can take an unfamiliar failure and follow it through layers of the stack to a root cause.
- Strong proficiency in at least one backend language (Python, Go, or C++), sufficient to read production code, write production-grade tests, and contribute infrastructure code directly.
- Excellent written and async communication. You operate effectively across time zones and in environments where most decisions get made in writing.
- Self-direction under ambiguity. You frame problems, make trade-off decisions, and push back when quality is at risk - without waiting to be asked.
- Experience with Cloud infrastructure, model serving systems, or GPU accelerated workloads is a strong plus.
- Experience using AI tooling (LLMs, coding assistants, agents) to accelerate test development, triage, or analysis is a plus.
People who are serious about software make their own hardware. At Cerebras we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:
- Build a breakthrough AI platform beyond the constraints of the GPU.
- Publish and open source their cutting-edge AI research.
- Work on one of the fastest AI supercomputers in the world.
- Enjoy job stability with startup vitality.
- Our simple, non-corporate work culture that respects individual beliefs.
Read our blog: Five Reasons to Join Cerebras in 2026.
Apply today and become part of the forefront of groundbreaking advancements in AI!Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.
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Skills Required
- 5+ years of experience in quality engineering or test engineering
- Deep cloud platform experience, preferably AWS
- Building scalable test infrastructure
- Strong proficiency in at least one backend language (Python, Go, or C++)
- Excellent written and async communication
Cerebras Systems Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cerebras Systems and has not been reviewed or approved by Cerebras Systems.
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Fair & Transparent Compensation — Pay is considered competitive for an AI‑hardware firm, and many employees are described as generally happy with compensation. Sentiment indicates compensation is viewed favorably while acknowledging variation by role and seniority.
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Healthcare Strength — Health coverage is described as top quality with medical, dental, and vision included. Premiums are reportedly fully covered for employees in some plans, increasing perceived value.
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Flexible Benefits — Work‑from‑home flexibility is regarded as strong. Flexible arrangements complement standard offerings like vacation, sick leave, and paid holidays.
Cerebras Systems Insights
What We Do
Cerebras Systems is a team of pioneering computer architects, computer scientists, deep learning researchers, functional business experts and engineers of all types. We have come together to build a new class of computer to accelerate artificial intelligence work by three orders of magnitude beyond the current state of the art. The CS-2 is the fastest AI computer in existence. It contains a collection of industry firsts, including the Cerebras Wafer Scale Engine (WSE-2). The WSE-2 is the largest chip ever built. It contains 2.6 trillion transistors and covers more than 46,225 square millimeters of silicon. The largest graphics processor on the market has 54 billion transistors and covers 815 square millimeters. In artificial intelligence work, large chips process information more quickly producing answers in less time. As a result, neural networks that in the past took months to train, can now train in minutes on the Cerebras CS-2 powered by the WSE-2. Join us: https://cerebras.net/careers/
