Senior Backend Engineer improving Tempo, Grafana Labs’ open - source distributed tracing backend. Owning scalable database systems, APIs, performance, and operational excellence for Grafana observability products.
About the role
- Kubernetes and HPC Engineer building scalable AI/ML and simulation infrastructure for Capgemini Engineering. Managing Kubernetes, HPC clusters, NVIDIA GPUs, automation, and cloud-native platforms.
Responsibilities
- Design, deploy, and manage Kubernetes-based compute platforms for AI/ML and HPC workloads
- Build and maintain scalable HPC environments utilizing workload schedulers
- Support and optimize NVIDIA GPU infrastructure for machine learning, data processing, and simulation workloads
- Implement infrastructure automation, CI/CD pipelines, and monitoring solutions to improve platform reliability and operational efficiency
- Manage containerized applications using Kubernetes, Docker, and Helm
- Troubleshoot and optimize cluster, network, storage, and application performance across distributed computing environments
- Collaborate with engineering, research, and AI teams to enable high-performance computing and cloud-native solutions
- Ensure platform scalability, availability, security, and operational excellence
Requirements
- 5+ years of experience in Kubernetes, Cloud Infrastructure, Platform Engineering, DevOps, or related fields
- Minimum 2+ years of experience supporting HPC or large-scale distributed compute environments
- Strong hands-on experience with Kubernetes (K8S), Docker, Helm, and container orchestration technologies
- Exposure to Trainium or Inferentia is highly preferred
- Experience managing HPC clusters and workload schedulers, including Slurm and/or Volcano
- Expertise with NVIDIA GPU infrastructure, GPU-enabled workloads, and performance optimization
- Strong Linux administration and troubleshooting skills
- Proficiency in Python and/or Bash scripting for automation and operational management
- Experience implementing CI/CD pipelines, monitoring, logging, and infrastructure automation solutions
- Hands-on experience with at least one major cloud platform, Azure AKS and Google Kubernetes Engine (GKE)
Benefits
- Paid time off based on employee grade (A-F): Vacation: 12-25 days, depending on grade
- Company paid holidays
- Personal Days
- Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
- Additional compensation such as variable incentives, bonuses, or commissions may be available depending on the position and applicable laws
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