Site Reliability Engineer

Description

The company builds full-stack AI, from frontier models and developer tools to applications and compute. It works with enterprises in finance, manufacturing, defense, healthcare and the public sector to design AI systems tailored to each client, which the client can run on its own terms.

The team is spread across Europe, North America, Asia and the Middle East. It describes itself as creative, low-ego and team-spirited.

Responsibilities

• Help set the reliability, scalability and performance of the platform and customer-facing applications, working with software engineers and research teams so that internal and external customers get what they need.
• Balance running production systems each day against longer-term engineering that cuts repetitive operational work and improves availability and performance.
• Build, run and maintain scalable, highly available, fault-tolerant infrastructure for web services and ML workloads.
• Keep the platform, inference and training environments available, and make work environments reproducible across several HPC clusters.
• Handle production issues as they arise, including interrupts, on-call work, user administration, data extraction and infrastructure scaling.
• Improve monitoring, alerting and incident response to keep systems performing well and downtime low.
• Build and maintain CI/CD, containerization, orchestration, monitoring, logging and alerting for client APIs and large training runs.
• Take part in on-call rotations from time to time, and run root cause analysis so incidents do not repeat.
• Keep improving infrastructure automation, deployment and orchestration with Kubernetes, Flux and Terraform.
• Work with AI/ML researchers on safe, reproducible model training experiments.
• Build a cloud-agnostic platform that shields researchers from the infrastructure beneath.
• Create workflows and tools, such as scripts, refactors, API features, web apps and dashboards, to raise reliability, availability and performance.
• Work with the security team so infrastructure follows security best practices and compliance requirements.
• Document processes and procedures so the team shares knowledge consistently.
• Contribute to open-source projects, research publications, blog articles and conferences.

Requirements

• Hold a Master's degree in computer science, engineering or a related field.
• Have 7+ years of experience in a DevOps or SRE role.
• Have strong experience with cloud computing and highly available distributed systems.
• Have worked on reliability problems in critical environments, including root cause analysis, troubleshooting live systems and on-call rotations.
• Have worked against reliability KPIs such as observability, alerting and SLAs.
• Have hands-on experience with CI/CD, containerization and orchestration tools such as Docker and Kubernetes.
• Know monitoring, logging, alerting and observability tools such as Prometheus, Grafana, ELK Stack and Datadog.
• Be familiar with infrastructure-as-code tools such as Terraform or CloudFormation.
• Be proficient in scripting languages such as Python, Go and Bash, and know software development best practices.
• Understand networking, security and system administration concepts.
• Solve problems well and communicate clearly.
• Be self-motivated and able to work well in a fast-paced startup.
• If you also have: experience in an AI/ML environment.
• If you also have: experience with high-performance computing systems and workload managers such as Slurm.
• If you also have: experience with modern AI-oriented solutions such as Fluidstack, Coreweave or Vast.

Conditions

Occasional participation in on-call rotations.

Benefits

• Benefits depend on country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances and other location-specific perks.
• The benefits page has the current details for each location.