Staff Software Engineer, Inference Platform

Fdetimes; Sunnyvale (CA); Presencial; USD 210.000 - 270.000; Jornada completa

Descripción de la vacante

Cerebras Systems is seeking a Staff Engineer to lead and contribute to the Inference Platform on the datacenter-scale cluster orchestration layer. You will work across Kubernetes operators, security policies, CI/CD, and platform evolution to deliver scalable, reliable AI inference.

You will shape technical direction, own major roadmap areas, and drive architectural decisions for high-availability systems with low latency and strong observability across global deployments.

Formación

• 8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.
• Deep expertise in distributed systems architecture, ideally with Kubernetes.
• Strong track record of making sound architectural decisions for 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++, with the expectation that you can contribute production code directly.
• Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.
• Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.
• Preferred Skills & Qualifications
• Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.

Responsabilidades

• Design, develop, test, and maintain production software, with responsibilities spanning testing, continuous development, observability, security, networking, debugging, and productionization.
• Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.
• Platform Direction. Help shape the technical direction for the Inference Platform, Kubernetes CRDs, 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. Improve latency, throughput, capacity, and resilience.
• Execution on Critical Paths. Write and review production code in key platform areas; make high-consequence architectural decisions.
• Production Leadership. Lead on hard production issues and bottlenecks; drive observability, incident response, and post-incident improvements.
• Technical Influence. Partner with ML, Product, Infrastructure, and Cloud teams to translate requirements into scalable designs.

Conocimientos

Distributed systems

Kubernetes

Backend development

System architecture

Security (TLS, mTLS)

Low-latency optimization

Go

C++

Observability

Herramientas

Kubernetes

Go

C++

TLS/mTLS

Descripción del empleo

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 Staff Engineer to help lead, drive, and 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.
• Raise the effectiveness of senior engineers through design feedback, pairing, and clear technical standards.
• 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

• 8+ years of experience in software engineering, with substantial individual contributor experience building and operating large-scale distributed systems or cloud infrastructure.
• Deep expertise in distributed systems architecture, ideally with Kubernetes.
• Strong track record of making sound architectural decisions for 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++, with the expectation that you can contribute production code directly.
• Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLO-driven operations.
• Ability to influence senior engineers and cross-functional partners through technical credibility, communication, and judgment, especially within your domain and adjacent systems.
• Preferred Skills & Qualifications
• Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads.

Location: Sunnyvale or Toronto preferred

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.

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.