18:I[34901,["/_next/static/chunks/1q_xs299ft_73.js","/_next/static/chunks/1hsg494-jz4os.js","/_next/static/chunks/1a25lc5cxtp8a.js","/_next/static/chunks/08v7mhpebw2l_.js"],"JobTable"] 19:T1eae,

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

As a Kernel Engineer at Cerebras, you will develop high-performance software at the intersection of hardware and software for cutting-edge artificial intelligence and high-performance computing workloads.

You will help implement, optimize, and validate machine learning and linear algebra operations for the Cerebras Wafer-Scale Engine, our custom massively parallel processor architecture. Working alongside experienced kernel, compiler, performance, and hardware engineers, you will learn how algorithms are mapped to specialized hardware and contribute to software that maximizes compute utilization and system performance.

You will be part of a team responsible for the design, development, performance tuning, and validation of foundational ML and HPC kernels. This is an excellent opportunity for a new graduate who is interested in computer architecture, parallel programming, low-level software, and machine learning systems.

Responsibilities

Help design and implement machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine.
Develop and debug high-performance kernel routines using low-level programming techniques and the Cerebras Software Language, a custom C-like language.
Apply parallel programming algorithms to map computational workloads efficiently onto the Cerebras architecture.
Use mathematical analysis, performance data, and profiling tools to evaluate kernel behavior and inform design decisions.
Identify and investigate correctness, performance, and hardware utilization issues.
Develop unit tests and system-level validation methodologies to verify the functionality and performance of kernel libraries.
Collaborate with kernel, compiler, performance, and hardware engineers to improve software and system performance.
Study emerging machine learning workloads and contribute to the evolution of the kernel library.
Participate in code reviews, technical discussions, and software development processes.
Build an understanding of the Cerebras architecture, instruction set, memory system, and communication model.

Minimum Skills & Qualifications

Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related field.
Strong programming fundamentals in C++ and familiarity with Python.
Understanding of foundational computer architecture concepts such as processors, memory hierarchies, instruction execution, or data movement.
Knowledge of data structures, algorithms, and software development fundamentals.
Experience debugging software through coursework, internships, research, co-op placements, or technical projects.
Strong analytical and problem-solving skills.
Interest in low-level software, parallel computing, performance optimization, or hardware/software co-design.
Ability to learn unfamiliar systems and collaborate effectively within a technical team.

Preferred Skills & Qualifications

Research, internships, or projects involving kernel development, compilers, computer architecture, HPC, or systems programming.
Familiarity with parallel algorithms, multithreaded programming, or distributed memory systems.
Exposure to programming accelerators such as GPUs, FPGAs, or other specialized processors.
Experience with low-level programming, assembly language, CUDA, OpenCL, or a domain-specific language.
Familiarity with machine learning concepts, neural networks, or frameworks such as PyTorch or TensorFlow.
Exposure to numerical computing, linear algebra, or HPC kernels.
Experience using profiling, benchmarking, or performance analysis tools.
Familiarity with library or API development practices.

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:

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.

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.

1a:T13b5,

About The Role

As a New Graduate Software Engineer, you will collaborate with world-class engineers to solve real-world challenges across the software stack. You will contribute to software systems that directly impact performance, scalability, reliability, and usability of next-generation AI infrastructure.

You will gain hands-on experience working across multiple layers of a fully integrated AI-accelerated system, including advanced hardware interfaces, low-level infrastructure, distributed systems, compilers, and ML frameworks.

Responsibilities

You will develop and maintain the infrastructure required to build, test, operate, simulate, and evaluate the Cerebras software stack. As a DevOps engineer, you will be responsible for designing efficient, scalable workflows for automating processes in the cloud and in our datacenter. You will work closely with the development and product management teams to monitor the quality and performance of the software that runs on the Wafer Scale Engine (WSE), the world’s largest and fastest AI computer. 

Required Qualifications

Enrolled in a University program with a degree in Computer Science, Computer Engineering, or other related disciplines.
Experience in software development environments.
Proficient in Python, shell scripting, Makefiles.
Strong end-to-end triage, debug, and troubleshooting skills.
Experience with Jenkins and other CI/CD platforms.
Experience with Docker, Kubernetes and container technology in general.
Experience building services on top of AWS or other cloud platforms at scale.
UI experience highly desirable.

Why Join 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.

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!

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

1b:T19ea,

About The Role

This role is ideal for candidates with a strong interest in systems programming, networking, embedded systems, distributed infrastructure, or performance-oriented software engineering. Our teams work very closely with hardware, so candidates with experience primarily focused on higher-level application development or AI applications may be less aligned with the nature of this work.

Responsibilities

Collaborate with experienced engineers on real-world systems and infrastructure challenges.
Design, implement, test, and debug software solutions that directly impact system performance and reliability.
Contribute to low-level software components interacting closely with hardware and networking infrastructure.
Learn and contribute across multiple layers of a fully integrated AI-accelerated platform.
Participate in debugging, performance optimization, and system bring-up activities.
Develop tools and infrastructure to improve observability, reliability, and scalability.
Work cross-functionally with hardware, firmware, compiler, and infrastructure teams.

Required Qualifications

Recently graduated or currently enrolled in a university program in Computer Science, Computer Engineering, Electrical Engineering, or a related discipline (graduating in 2026).
Proficiency in C/C++ programming languages
Interest or exposure to systems/socket programming, networking, embedded systems, operating systems, device drivers, distributed systems, or network performance.
Desire to work close to hardware/network and learn low-level engineering concepts.
Detail-oriented but keen to learn the bigger picture and step out of comfort zone.
Excellent communication and collaboration skills.
Hybrid role based in Toronto, ON, or Sunnyvale CA

Assets

Experience with Linux systems programming or debugging tools.
Familiarity with TCP/RDMA protocols, RPCs, and packet trace tools such as Wireshark
Exposure to networking concepts, device drivers, embedded systems, or distributed infrastructure.
Familiarity with performance optimization or concurrent programming concepts.
Interest in large-scale AI infrastructure and accelerated computing systems.

Why Join 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.

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!

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

1c:T1371,

About The Role

Engineers in the CoDesign and NextGen organization work at the interface of software and hardware helping everything from high performance kernel design, next generation ASIC performance modeling and tuning, new system bringup and software tuning, system robustness and simulations.

As an new engineer you'll be expected to learn the Cerebras products and platforms end to end starting at the base layer of programming the Wafer Scale Engine through kernel development, modeling performance for our software products and validating the work through exercising it on both actual hardware and simulations.

Skills & Qualifications

MS/BS in Computer Engineer, Electrical Engineering or Computer Science
Strong background in computer architecture
Strong analytical and problem solving mindset
Exposure to CPU/GPU Architecture and programming models
Experience working on CPU/GPU simulators
Exposure to performance profiling and debug on any system pipeline
Experience with C++ and Python
Exposure to and basic understanding of machine learning is desired

Location

This is a full-time, in-office position based in Sunnyvale, CA. We offer relocation support for candidates relocating to the Bay Area.

Base salary range: $145,000-$155,000 annually, depending on experience, skills, and qualifications, plus equity.

Why Join 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.

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!

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

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Role	Company	Location	Season	Posted
Kernel Engineer - New Grad	Cerebras	United StatesHybrid	—	1 month ago
DevOps Engineer - New Grad 2026	Cerebras	Toronto OfficeHybrid	—	3 months ago
Software Engineer - New Grad 2026	Cerebras	Toronto OfficeHybrid	—	3 months ago
CoDesign & NextGen - New College Grad	Cerebras	Headquarters/Sunnyvale OfficeOn-site	Summer 2026	8 months ago