Cerebras Systems Inc. Logo

Cerebras Systems Inc.

AI Inference Core - Software Integration Engineer

Posted 2 Days Ago
Remote
Hiring Remotely in Canada
Mid level
Remote
Hiring Remotely in Canada
Mid level
Integrate, validate, and productionize cross-stack inference features across AI frameworks, runtime, compiler, kernels, distributed systems, and hardware. Drive zero-to-one projects, debug system-wide failures, manage accelerated timelines, and improve automation, diagnostics, and repeatable integration practices while collaborating across software and hardware teams.
The summary above was generated by AI

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; 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.
Cerebras works with the leading 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.

About the Role

We are looking for a Software Integration Ninja to join the AI Inference Core team at Cerebras. This team sits at the intersection of AI infrastructure, distributed systems, compilers, runtimes, kernels, and hardware/software co-design.

The Innovation Engine for Inference Core — turning ideas into reality.

You will help take ambitious ideas from concept to working reality across the Cerebras inference stack. You will integrate and validate cross-component projects of high complexity, often on accelerated timelines, and work directly with engineers across AI, runtime, compiler, kernel, systems, and hardware teams.

A Special Task Force, Not a Typical Engineering Role
  • Zero-to-one mission: Take incomplete ideas and early prototypes all the way to working, validated capabilities.

  • Cross-stack complexity: Move across AI frameworks, runtime, compiler, kernels, distributed systems, infrastructure, and hardware—not just one component or codebase.

  • Accelerated and dynamic cadence: Expect focused daily syncs, rapidly changing priorities, and periods of intense integration work. This is not a role for engineers seeking strictly regular, predictable work hours.

  • Comfortable on the hot seat: Take ownership when the path is unclear, make sound decisions with incomplete information, and stay effective when timelines are tight.

  • Bias for action: At critical moments, the mindset is “No Process, No Documentation, Just Get Stuff Done!!!” Cut through unnecessary ceremony, deliver the result, and then turn what you learned into better automation, diagnostics, documentation, and repeatable practices.

  • Team multiplier: Always push the work forward while raising the pace, clarity, and effectiveness of the people around you. We want people who bring the team with them—not lone heroes.

We prefer candidates with experience in software/hardware co-design or other complex systems, but that experience is not required. We welcome exceptional junior engineers who are eager to learn, do not shy away from ambiguity or hard work, and can demonstrate strong fundamentals, curiosity, ownership, and persistence.

What You Will Do
  • Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform.

  • Take high-value projects from zero to one—from an incomplete idea or prototype to a working, validated capability.

  • Integrate and validate software components spanning AI frameworks, runtime, compiler, kernels, distributed systems, and hardware.

  • Drive cross-component projects of high complexity from problem definition through integration, validation, and release readiness.

  • Collaborate closely with software and hardware engineers to make co-design trade-offs and resolve system-level issues.

  • Investigate and debug difficult failures across large-scale AI workloads, distributed software, infrastructure, and hardware boundaries.

  • Work effectively on accelerated timelines while keeping technical risks, dependencies, and decisions visible.

  • Participate in focused daily syncs, manage rapidly changing priorities, and drive ambiguous situations toward concrete outcomes.

  • Identify bottlenecks, failure modes, edge cases, and integration gaps that affect inference correctness, performance, or delivery.

  • Capture the essential lessons from urgent work so the next integration is faster and less chaotic.

  • Create momentum beyond your own work by helping teammates move faster, make better decisions, and close difficult problems together.

Minimum Skills & Qualifications
  • Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.

  • Demonstrated ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.

  • Experience—through professional work, internships, research, academic projects, open source, or equivalent hands-on work—building or debugging software systems.

  • Curiosity about how complex systems behave across component boundaries.

  • Willingness to read unfamiliar code, learn new layers of the stack, and take ownership beyond a narrowly defined area.

  • Ability to work hard and stay effective during periods of uncertainty, rapid change, and accelerated delivery.

  • Clear communication and strong collaboration across disciplines and levels of experience.

Preferred Skills
  • Experience in a startup or similarly fast-moving, resource-constrained engineering environment.

  • Demonstrated experience taking a project from zero to one: turning an ambiguous problem, early idea, or prototype into a working and reliable capability.

  • Experience with software/hardware co-design, hardware accelerators, compilers, kernels, runtimes, or low-level systems.

  • Experience debugging complex systems, distributed software environments, or large-scale compute clusters.

  • Experience with AI infrastructure, model deployment, LLMs, or multimodal workloads.

  • Exposure to performance debugging, profiling, observability, or failure analysis.

  • Familiarity with microservices, containers, cluster orchestration, cloud infrastructure, or high-performance computing.

  • Track record of driving cross-team projects from an incomplete idea to a reliable working result.

Location
  • This role follows a hybrid schedule and requires in-office presence three days per week. Fully remote work is not available.

  • Office locations: Sunnyvale, CA or Toronto, ON.

Why Join Cerebras

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:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.

  2. Publish and open source their cutting-edge AI research.

  3. Work on one of the fastest AI supercomputers in the world.

  4. Enjoy job stability with startup vitality.

  5. Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!

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.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

Similar Jobs

10 Hours Ago
Remote
Canada
Expert/Leader
Expert/Leader
Artificial Intelligence • Software
Lead full-cycle strategic sales in Canada for Fieldguide, building relationships with major audit and advisory firms. Drive net-new revenue, orchestrate multi-regional account strategy, manage complex technical sales cycles, deliver executive presentations, coordinate cross-functional stakeholders, develop international playbooks, and represent the company at industry events. Expected travel up to 30%.
10 Hours Ago
Remote or Hybrid
CA
Senior level
Senior level
Gaming
Lead development of core client systems and engine-level infrastructure in Unity/C#. Diagnose and fix cross-cutting performance issues, upgrade third-party SDKs, evolve build tooling, produce design docs, scope multi-week infrastructure initiatives, mentor engineers, and drive profiling, optimization, and architecture changes to enable future features.
Top Skills: AndroidAWSC#DatadogGitiOSKubernetesUnity
10 Hours Ago
Easy Apply
Remote or Hybrid
Canada
Easy Apply
Senior level
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Own and optimize Okta identity infrastructure and Google Workspace, build Workato automations (OWL-IT), support IAM initiatives (RBAC, provisioning, SCIM), act as Tier 3 escalation for identity incidents, ensure StateRAMP/FedRAMP compliance, document runbooks, and collaborate with Security/GRC to strengthen identity security.
Top Skills: ConfluenceGemini EnterpriseGoogle Apps Manager (Gam)Google Cloud Platform (Gcp)Google WorkspaceIgaOktaOkta WorkflowsOwl-ItPamPythonRbacRest ApisSaviyntScimSplunkSsoTerraformVertex AiWorkatoWorkato Connector SdkWorkato One

What you need to know about the Ottawa Tech Scene

The capital city of Canada and the nation's fourth-largest urban area, Ottawa has proven a rapidly growing global tech hub. With over 1,800 tech companies, many of which are leaders in their sectors, the city's tech talent now makes up more than 13 percent of its total workforce. This growth is driven not only by the big players like UL Solutions and Dropbox, but also by a thriving startup ecosystem, as new businesses emerge to follow in the footsteps of those that came before them.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account