Cerebras

2 months ago

Sr. Member of Technical Staff

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Design and build software features that improve system resiliency and high availability for distributed AI inference services. Develop AWS-based deployment workflows, Python scripts and APIs for real-time inference preprocessing/execution/post-processing, and automation to detect and mitigate failure modes. Work with Docker, Kubernetes, and monitoring/observability tooling to ensure scalable, low-latency performance, while debugging deployment and networking issues and documenting workflows, APIs, and release notes.

Location: Sunnyvale

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Design and develop features for system resiliency and high availability, including automated recovery mechanisms and fault-tolerant distributed architectures.
•Build and maintain AWS-based cloud deployment workflows for low-latency, scalable AI inference performance.
•Develop Python scripts and APIs for real-time inference data preprocessing, inference execution, and post-processing.
•Use parallel programming (multi-threading and asynchronous processing) to maximize resource efficiency on AWS compute instances.
•Develop and operate inference services using Docker and Kubernetes, including orchestration strategies, debugging, and defect triage using logs/metrics/traces.

Key Requirements

•Master’s degree (or foreign equivalent) in Computer Science or a related field.
•18 months of experience as an Information Security Analyst, Software Engineer, Sr. Member of Technical Staff, IT Senior Applications Engineer, or related occupation.
•Infrastructure-as-Code and deployment automation experience with Terraform, AWS CloudFormation, AWS CDK, and Ansible.
•Containerization and orchestration experience with Docker, Kubernetes, AWS EKS/ECS, AWS Fargate, and Helm.
•Programming and observability skills including Python, Node.js/JavaScript/Flask, and monitoring/logging/distributed tracing with CloudWatch, X-Ray, ELK, Prometheus, and Grafana.

Experience:1+ yearsAIInferenceCloudDistributed systems

Education:Master's in Computer Science (or a related field)

Skills:CollaborationTroubleshootingDocumentationAutomation mindset

Tech Stack:AWSTerraformAWS CloudFormationAWS CDKAnsibleDockerKubernetesAWS EKSAWS Elastic Container Service (ECS)AWS FargateHelmAWS EC2AWS LambdaAuto Scaling GroupsAWS CloudWatchAWS X-RayELK (Elasticsearch, Logstash, Kibana)PrometheusGrafanaPython

Company Brief

Cerebras

Designs and builds wafer-scale AI accelerators and systems for large-scale deep learning workloads, delivering specialized hardware and software to accelerate model training and inference for enterprises and research institutions.

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn

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Cerebras

2 months ago

Sr. Member of Technical Staff

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: Sunnyvale

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Seniority: Mid level

Key Responsibilities

•Design and develop features for system resiliency and high availability, including automated recovery mechanisms and fault-tolerant distributed architectures.
•Build and maintain AWS-based cloud deployment workflows for low-latency, scalable AI inference performance.
•Develop Python scripts and APIs for real-time inference data preprocessing, inference execution, and post-processing.
•Use parallel programming (multi-threading and asynchronous processing) to maximize resource efficiency on AWS compute instances.
•Develop and operate inference services using Docker and Kubernetes, including orchestration strategies, debugging, and defect triage using logs/metrics/traces.

Key Requirements

•Master’s degree (or foreign equivalent) in Computer Science or a related field.
•18 months of experience as an Information Security Analyst, Software Engineer, Sr. Member of Technical Staff, IT Senior Applications Engineer, or related occupation.
•Infrastructure-as-Code and deployment automation experience with Terraform, AWS CloudFormation, AWS CDK, and Ansible.
•Containerization and orchestration experience with Docker, Kubernetes, AWS EKS/ECS, AWS Fargate, and Helm.
•Programming and observability skills including Python, Node.js/JavaScript/Flask, and monitoring/logging/distributed tracing with CloudWatch, X-Ray, ELK, Prometheus, and Grafana.

Experience:1+ yearsAIInferenceCloudDistributed systems

Education:Master's in Computer Science (or a related field)

Skills:CollaborationTroubleshootingDocumentationAutomation mindset

Company Brief

Cerebras

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn