Software Engineer, Inference Platform at Cerebras Systems

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

18 Sep, 26

Salary

0.0

Posted On

20 Jun, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Distributed Systems, Kubernetes, Go, C++, Cloud Infrastructure, ML Inference, Security, Latency Optimization, High-QPS Systems, CI/CD, Observability, Networking

Industry

Semiconductor Manufacturing

Description

Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. Our novel wafer-scale architecture provides the AI compute power of dozens of GPUs on a single chip, with the programming simplicity of a single device. This approach allows Cerebras to deliver industry-leading training and inference speeds and empowers machine learning users to effortlessly run large-scale ML applications, without the hassle of managing hundreds of GPUs or TPUs. Cerebras' current customers include top 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. Thanks to the groundbreaking wafer-scale architecture, Cerebras Inference offers the fastest Generative AI inference solution in the world, 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. Location: Sunnyvale 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 which glues together the cloud components to the ML components. We are often the first team to face issues that haven’t been solved yet so we get to lead the company on a wide variety of solutions, from k8s operators to security policies of services and CI/CD. This is a hands-on role for an engineer who will split their time between design and coding and should be experienced in all facets of development including; testing, continuous development, observability, security, networking, debugging, productionization. If you're interested in building our next-generation architecture of a globally distributed inference platform, we'd like to talk. Responsibilities Platform Direction. Help shape the technical direction for the Inference Platform, k8s 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, C++. Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads is a plus. 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. Read our blog: Five Reasons to Join Cerebras in 2026. 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.

Responsibilities

The role involves designing and coding the orchestration layer for a globally distributed inference platform. Responsibilities include shaping technical direction, ensuring system reliability, and partnering with cross-functional teams to scale AI workloads.