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Cerebras

AI accelerator hardware replacing GPUs

Senior Software Engineer - Inference Cloud

Platform Engineering +1Confirmed live in the last 24 hours
Full-timeSunnyvale, CA, USANo salary listedIn-person

About the Job

Requirements

  • At least 5 years of software engineering experience, including building and operating production services or cloud infrastructure.
  • Strong Kubernetes expertise, including workload lifecycle, networking, service discovery, storage, autoscaling, and troubleshooting cluster and application failures.
  • Hands-on experience with Amazon EKS or a comparable managed Kubernetes service.
  • Experience configuring and troubleshooting Envoy and Istio, or comparable proxy and service mesh technologies, and a solid understanding of HTTP, gRPC, DNS, TLS, and mTLS.
  • Experience developing services that use production databases, with practical knowledge of query optimization, indexing, connection management, and database reliability.
  • Strong programming skills in Go or another backend or systems language, with the ability to write, test, and maintain production software.
  • Experience with infrastructure as code and automated deployment workflows using Terraform, Argo CD, Kustomize, or equivalent tools.
  • Experience diagnosing performance and reliability issues using metrics, logs, and tracing.
  • Ability to independently deliver projects, explain technical tradeoffs, and collaborate effectively across engineering teams.

Responsibilities

  • Build and improve production Kubernetes environments on Amazon EKS, including workload scheduling, autoscaling, cluster upgrades, resource utilization, network policies, and failure recovery.
  • Develop and operate traffic management infrastructure using Envoy and Istio; improve routing, rate limiting, connection management, timeouts, retries, and failover to keep services responsive under changing demand.
  • Build database-backed services and improve the reliability and performance of their data stores; troubleshoot query performance, connection pooling, and availability issues, and strengthen backup and recovery practices.
  • Identify bottlenecks across applications, Kubernetes, networking, and databases; improve latency, throughput, and capacity efficiency in high-QPS systems, including during traffic spikes and partial failures.
  • Use Terraform, Argo CD, and Kustomize to automate infrastructure provisioning and application delivery; improve deployment validation, rollback, and operational tooling.
  • Build actionable metrics, logs, traces, dashboards, and alerts; investigate incidents, deliver lasting fixes, and contribute to design reviews, code reviews, and shared engineering practices.
  • Design and own cloud components, improve request routing and service connectivity, work with production databases, and debug issues across the stack.
  • Take projects from design through rollout and ongoing operation, partnering closely with ML, Product, and Infrastructure teams.

Desired Qualifications

  • AWS networking experience, including VPNs, Transit Gateway (TGW), Direct Connect (DX), VPC routing, and security groups.
  • Experience designing distributed systems, including replication, consistency, fault tolerance, and multi-region operation.
  • Production programming experience in C++.
  • Experience optimizing latency, throughput, and efficiency in high-QPS systems.
  • Experience reducing time to first token (TTFT) and tail latency.
  • Familiarity with ML inference infrastructure or model serving systems.

About the Company

Cerebras

AI accelerator hardware replacing GPUs

Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.

Company size
501-1,000
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
2016

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