C

Cerebras

AI accelerator hardware replacing GPUs

Software Integration Engineer - AI Inference Core

Systems Software EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Strong software-engineering fundamentals and programming ability in Python, C++, Go, or a similar language.
  • 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, large language models, or multimodal workloads.
  • Exposure to performance debugging, profiling, observability, or failure analysis.
  • Familiarity with microservices, containers, cluster orchestration, cloud infrastructure, or high-performance computing.
  • Hands-on experience building or debugging software systems through professional work, internships, research, academic projects, open source, or equivalent experience.
  • Ability to communicate clearly and collaborate across disciplines and levels of experience.

Responsibilities

  • Turn new inference ideas and features into integrated, working capabilities across the Cerebras platform.
  • Take high-value projects from zero to one, developing an incomplete idea or prototype into a working, validated capability.
  • Integrate and validate software components spanning AI frameworks, runtime, compiler, kernels, distributed systems, and hardware.
  • Drive complex cross-component projects from problem definition through integration, validation, and release readiness.
  • Collaborate 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 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 affecting inference correctness, performance, or delivery.
  • Capture essential lessons from urgent work to make subsequent integration faster and more reliable.
  • Help teammates move faster, make better decisions, and resolve difficult problems together.

Desired Qualifications

  • Experience in a startup or similarly fast-moving, resource-constrained engineering environment.
  • Experience taking a project from zero to one by turning an ambiguous problem, early idea, or prototype into a working and reliable capability.
  • Ability to break down ambiguous technical problems, form hypotheses, gather evidence, and drive issues to resolution.
  • 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 remain effective during uncertainty, rapid change, and accelerated delivery.
  • Track record of driving cross-team projects from an incomplete idea to a reliable working result.

About the Company

Cerebras

AI accelerator hardware replacing GPUs

Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.

Company size
501-1,000
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
2016

Recently Posted Jobs

Explore more opportunities at Cerebras

See more jobs