ML Systems Performance Engineer
- Level
- Mid
Not stated in the posting: salary, work type, visa.
Open. First seen 3 October 2026.
About the role
Cerebras Systems's standard text
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
Engineers on the inference performance team operate at the intersection of hardware and software, driving end-to-end model inference speed and throughput. Their work spans low-level kernel performance debugging and optimization, system-level performance analysis, performance modeling and estimation, and the development of tooling for performance projection and diagnostics.
Responsibilities
- Build performance models (kernel-level, end-to-end) to estimate the performance of state of the art and customer ML models.
- Optimize and debug our kernel micro code and compiler algorithms to elevate ML model inference speed, throughput and compute utilization on the Cerebras WSE.
- Debug and understand runtime performance on the system and cluster.
- Develop tools and infrastructure to help visualize performance data collected from the Wafer Scale Engine and our compute cluster.
Requirements
- Bachelors / Masters / PhD in Electrical Engineering or Computer Science.
- Strong background in computer architecture.
- Exposure to and understanding of low-level deep learning / LLM math.
- Strong analytical and problem-solving mindset.
- 3+ years of experience in a relevant domain (Computer Architecture, CPU/GPU Performance, Kernel Optimization, HPC).
- Experience working on CPU/GPU simulators.
- Exposure to performance profiling and debug on any system pipeline.
- Comfort with C++ and Python.
Cerebras Systems's standard text
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.
What this role asks for
Particular to this role
Deep Learning
Rare in Cerebras Systems's other 100 open postings.
Standard for data science / ML roles
LLM
Common in data science / ML postings at any company.
In most of Cerebras Systems's ads
Python
Named in most of its open postings, whatever the role.
38% of this description is written for the role. The rest is Cerebras Systems's standard text, folded away below.
Read against Cerebras Systems's other open postings on this site.
The team: Inference Core HIRES STEADILY
This role is one of 13 open in Inference Core. 3 were posted in the last 30 days and the oldest in July: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (13 of 13), C++ (10 of 13), LLM (6 of 13), Machine Learning (6 of 13), PyTorch (6 of 13), Deep Learning (4 of 13), CUDA (3 of 13)
OTHER ROLES ON THIS TEAM
- ML Research Scientist - Inference ML posted Oct 2
- ML Algorithm Mapping and Performance Engineer, Core ML posted Sep 28
- ML Runtime and Kernel Engineer - Core ML posted Sep 28
- AI Inference Core - Infrastructure SW Engineer posted Sep 15
- AI Inference Core - Senior SW Engineer for Platform & DevOps posted Sep 3
- AI Inference Core - SDET Technical Lead, Release Integration Testing posted Sep 3
- ML Systems Performance Engineer posted Jun 16
- Kernel Engineer posted Feb 23
- ML Software Tool Development Engineer posted Feb 17
- AI Inference Core - Software Integration Engineer posted Feb 5
- Senior Runtime Engineer posted Oct 28
- Full Stack LLM Engineer posted Jul 18
From the team and dates on Cerebras Systems's own job board.
Similar jobs
- Senior ML Engineer (Agentic Search) at Nebius
Shares 4 skills: Deep Learning, C++, LLM… - Lead ML & AI Engineer at Here Technologies
Shares 4 skills: Deep Learning, C++, LLM… - Senior Machine Learning Engineer (Large Systems) at Graphcore
Shares 4 skills: Deep Learning, C++, LLM… - ML Engineer, Motion Planning at DiDi Labs
Shares 3 skills: Deep Learning, C++, Python · same seniority - ML Data Infrastructure Engineer at Cognitiv
Shares 3 skills: Deep Learning, LLM, Python · same seniority - Supplier Quality Engineer - New Grad at Cerebras Systems
Also at this company
Is this your posting and you want it taken down? Email info@careerholo.com.