Senior Runtime Engineer
Cerebras is hiring a Senior Runtime Engineer. Level rates it ; you can apply on Cerebras.
Level's read on this job
- On Level's scale, this role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions OpenAI, PyTorch and AI research among its tools and skills.
- Level classes it as a senior role.
- Cerebras has 121 other open roles on Level.
AI in this 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
We are building the next generation of large-scale AI systems that power training and inference workloads at unprecedented scale and efficiency.
You will design and develop high-performance distributed software that orchestrates massive compute and data pipelines across heterogeneous clusters. Your work will push the limits of concurrency, throughput, and scalability—enabling efficient execution of models at massive scale. This role sits at the intersection of systems engineering and machine learning performance, demanding both architectural depth and low-level implementation skills. You will help shape how models are executed and optimized end-to-end, from data ingestion to distributed execution, across cutting-edge hardware platforms.
We’re hiring for runtime roles across both Training and Inference.
Responsibilities
Design and implement distributed runtime components to efficiently manage large-scale execution workloads.
Develop and optimize high-performance data and communication pipelines that fully utilize CPU, memory, storage, and network resources.
Enable scalable execution across multiple compute nodes, ensuring high concurrency and minimal bottlenecks.
Collaborate closely with ML and compiler teams to integrate new model architectures, training regimes, and hardware-specific optimizations.
Diagnose and resolve complex performance issues across the software stack using profiling and instrumentation tools.
Contribute to overall system design, architecture reviews, and roadmap planning for large-scale AI workloads.
Skills & Qualifications
3+ years of experience developing high-performance or distributed system software.
Strong programming skills in C/C++, with expertise in multi-threading, memory management, and performance optimization.
Experience with distributed systems, networking, or inter-process communication.
Solid understanding of data structures, concurrency, and system-level resource management (CPU, I/O, and memory).
Proven ability to debug, profile, and optimize code across scales—from threads to clusters.
Bachelor’s, Master’s, or equivalent experience in Computer Science, Electrical Engineering, or related field.
Preferred Skills & Qualifications
Familiarity with machine learning training or inference pipelines, especially distributed training and large-model scaling.
Exposure to Python and PyTorch, particularly in the context of model training or performance tuning.
Experience with compiler internals, custom hardware interfaces, or low-level protocol design.
Prior work on high-performance clusters, HPC systems, or custom hardware/software co-design.
Deep curiosity about how to unlock new levels of performance for large-scale AI workloads.
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.
How we rate this
Senior Runtime Engineer at Cerebras rates 98 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Walk me through how you've used OpenAI in your day-to-day work.
- What are the limits of PyTorch that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Research, OpenAI, and PyTorch. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new software engineering jobs (Builds AI ●●●●) by email
One email a week with the new software engineering jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Software Engineering roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step