Cerebras
Staff Kernel Optimzation Engineer
Remote — the employer does not say where candidates may be based.
Location not stated
Employer listed it 8 months ago · Added today
Been open since 8 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
Not stated
Location
Location not stated
Timezone
Not stated
Contract
Full-time
Experience
Lead
Category
Software
This employer didn't state pay. Jobs like this usually pay around $200k–$275k a year, a typical range taken from 596 lead-level software roles on Nomaders that do state pay. It's a guide, not an offer.
Remote flexibility
Undisclosed
The listing is advertised as remote but does not state which countries or regions candidates may work from.
Why this role is Undisclosed
We only label a role Work from anywhere, Region restricted or Work from home when the employer's own wording says so. We checked this advert under our current rules and found no country or region eligibility requirement in it. We don't guess, so it stays Undisclosed until the employer publishes enough location information. Here is exactly what the advert left out.
- Countries you can work from: Not stated. The advert only gives "Remote", which names no country you must live in.
- Whether the work is remote: Never mentioned. The role reached us through a remote job board, but the advert itself doesn't say the work is remote.
- Working hours: Not stated. No timezone overlap or set hours are mentioned, so assume nothing either way.
Worth a look all the same. Missing wording is usually a rushed job posting rather than a closed door, so ask where you can be based in your first message, before you write a tailored application.
What the employer says
- Source listing states candidate location: "Remote"
What Nomaders makes of it
- No residency or region requirement found in the job description
- Check with the employer before assuming you can work from abroad
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
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 on our team, you will develop high-performance software solutions at the intersection of hardware and software, developing high-performance software for cutting-edge AI and HPC workloads. Your focus will be on implementing, optimizing, and scaling deep learning operations to fully leverage our custom, massively parallel processor architecture. You will be part of a world-class team responsible for the design, performance tuning, and validation of foundational ML and HPC kernels. This includes building a library of parallel and distributed algorithms that maximize compute utilization and push the boundaries of training efficiency for state-of-the-art AI models. Your work will be critical to unlocking the full potential of our hardware and accelerating the pace of AI innovation. Responsibilities
Develop design specifications for new machine learning and linear algebra kernels and mapping to the Cerebras WSE System using various parallel programming algorithms.
Develop and debug kernel library of highly optimized low level assembly instruction and C-like domain specific language routines to implement algorithms targeting the Cerebras hardware system.
Develop and debug high-performance kernel routines in low-level assembly and a custom C-like (CSL) language, implementing algorithms optimized for the Cerebras hardware system.
Using mathematical models and analysis to measure the software performance and inform design decisions.
Develop and integrate unit and system testing methodologies to verify correct functionality and performance of kernel libraries.
Study emerging trends in Machine Learning applications and help evolve Kernel library architecture to address computational challenges of the start-of-the-art Neural Networks.
Interact with chip and system architects to optimize instruction sets, microarchitecture, and IO of next generation systems.
Skills And Qualifications
Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.
Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.
Skilled in C++ and Python programming languages.
Good knowledge of library and/or API development best practices.
Strong debugging skills and knowledge of debugging complex software stack.
Preferred Skills And Qualifications
Experience in kernel development and/or testing.
Familiarity with parallel algorithms and distributed memory systems.
Experience in programming accelerators such as GPUs and FPGAs.
Familiarity with Machine Learning neural networks and frameworks such as TensorFlow and PyTorch.
Familiarity with HPC kernels and their optimization.
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.
Requirements
- ·Bachelor’s, Master’s, PhD or foreign equivalents in Computer Science, Computer Engineering, Mathematics, or related fields.
- ·Understanding of hardware architecture concepts — must be comfortable learning the details of a new hardware architecture.
- ·Skilled in C++ and Python programming languages.
- ·Good knowledge of library and/or API development best practices.
- ·Strong debugging skills and knowledge of debugging complex software stack.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, undisclosed, matches where you plan to live and work.
- 2Tailor your CV to the role at Cerebras, mentioning your remote working experience.
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 22h ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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