Software Engineer, Cluster Deployment
1 мес. назад
JuniorOnsite
pythonbashansiblelinuxkubernetesnetworking
Build and operate software systems for deploying and managing AI compute clusters worldwide.
Условия
- People who are serious about software make their own hardware. At , 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 :
- 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.
- Find out more about what it's like to work at here !
- Apply today and become part of the forefront of groundbreaking advancements in AI!
- 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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Другое
- Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows 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. works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with , to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
- About the Role
- We build and operate the software systems that deploy, validate, and manage AI compute clusters across data centers worldwide for the world’s fastest AI Inference. Our work turns complex bare-metal infrastructure into repeatable, automated deployment flows spanning server provisioning, network configuration, Kubernetes bring-up, health validation, and operational handoff.
- As a Software Engineer on the Cluster Deployment Automation team, you will help build the pushbutton tooling that makes large-scale cluster deployments faster, safer, and more reproducible. This role is designed for talented engineers passionate about learning through hands-on work with Python, Bash, Ansible, Linux, bare-metal servers, networking equipment, Kubernetes, and observability systems while learning how production AI infrastructure is built and operated at scale.
- Responsibilities
- Develop and maintain automation for deployment workflows, including provisioning, configuration, validation, and operational handoff.
- Turn manual deployment steps into tested, repeatable pushbutton workflows.
- Participate in hands-on cluster deployments to build practical debugging and operational expertise.
- Troubleshoot issues across Linux systems, bare-metal servers, networking, storage, Kubernetes, and connectivity.
- Contribute to infrastructure-as-code and GitOps workflows using tools such as Terraform, Ansible, pull requests, and code review.
- Add health checks, observability, dashboards, and validation logic to improve deployment reliability.
- Partner with networking, infrastructure, security, and operations teams to deliver secure and reproducible data center deployments.
- Basic Qualifications
- 2+ years of mid- to large-scale data center deployment
- Strong fundamentals in Python and Bash, with the ability to write scripts and small programs.
- Basic Linux experience, including command-line usage, processes, filesystems, and disk troubleshooting.
- Working knowledge of Git, including branching, commits, pull requests, and code review.
- CS, ECE, or related technical degree, or equivalent practical experience.
- Curiosity, strong problem-solving instincts, and willingness to work hands-on with real infrastructure.
- Preferred Qualifications
- Networking fundamentals, including VLANs and routing basics; exposure to BGP, switch configuration, or Arista EOS automation is a plus.
- Kubernetes experience or familiarity.
- Infrastructure-as-code and GitOps experience, including Terraform, Ansible, and PR-based change control.
- Bare-metal provisioning concepts such as PXE, DHCP, iPXE, Redfish, IPMI, and BMC management.
- Observability experience with Prometheus or Grafana.
- API design and client-server architecture.
- Automation side projects or open-source contributions.