Level

Cerebras

Software Engineer, Inference Platform

Cerebras is hiring a Software Engineer, Inference Platform in Sunnyvale, United States. Level rates it ; you can apply on Cerebras.

Level's read on this job

  • Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
  • The posting mentions OpenAI, Kubernetes and Docker among its tools and skills.
  • Level classes it as a mid-level role.
  • Cerebras has 121 other open roles on Level.

AI in this role

Design and scale a distributed inference platform and orchestration layer for high-speed AI chips and datacenter clusters.

openaikubernetesdockerpython
ai-researchdistributed-systemsinference-platformobservabilitynetworkingci-cd

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're hiring a Software Engineer to help contribute to projects on our Inference Platform team. Our team primarily owns the orchestration layer that runs inference on our datacenter clusters, connecting cloud components with machine learning services. We are often the first team to face problems that haven't been solved yet, leading solutions across Kubernetes operators, service security policies, and CI/CD.

If you're interested in building the next-generation architecture of a globally distributed inference platform, we'd like to talk.

Responsibilities

  • Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.

  • Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes custom resource definitions, failure domains, service boundaries, and system evolution over time, and own the roadmap for major technical areas.

  • Reliability & Performance. Architect active-active systems with rapid failover, graceful degradation, and clear SLOs. Drive system-level improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.

  • Execution on Critical Paths. Write and review production code in the most important parts of the platform. Make high-consequence architectural decisions within your area and set the technical bar through design reviews, code reviews, and sound engineering judgment.

  • Production Leadership. Lead on the hardest production issues and cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.

  • Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate product and business requirements into scalable system designs, and drive alignment on shared technical decisions within your domain and adjacent platform surfaces.

Skills & Qualifications

  • 3+ years of experience in software engineering, with experience building and operating large-scale distributed systems or cloud infrastructure.

  • Experience in distributed systems, ideally with Kubernetes.

  • Experience building highly available, latency-sensitive systems at scale.

  • Experience with security (certificates, TLS, mTLS).

  • Experience optimizing latency, throughput, and efficiency in high-QPS systems. Experience with TTFT and tail-latency reduction is a strong plus.

  • Strong proficiency in backend or systems languages such as Go or C++.

Preferred Skills & Qualifications

  • Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.

Location: Open to Sunnyvale or Toronto.

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:

  1. Build a breakthrough AI platform beyond the constraints of the GPU.

  2. Publish and open source their cutting-edge AI research.

  3. Work on one of the fastest AI supercomputers in the world.

  4. Enjoy job stability with startup vitality.

  5. 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.

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How we rate this

Software Engineer, Inference Platform at Cerebras rates 85 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.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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

AI ResearchDistributed SystemsInference PlatformObservabilityNetworkingCI/CDOpenAIKubernetes

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Tell me about a project where distributed systems was part of your work. What did you do?
  3. Tell me about a project where inference platform was part of your work. What did you do?
  4. Tell me about a project where observability was part of your work. What did you do?
  5. Tell me about a project where networking was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Research, Distributed Systems, Inference Platform, Observability, and Networking. 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.

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