Machine Learning Systems Administrator / DevOps Engineer: Training Clusters & Inference Cloud

Experience with Linux system administration, user and access management, and automation

Demonstrated expertise in scripting languages for system tooling and automation (bash, Python, etc.)

Experience with containers (Docker) and scheduling/orchestration systems (Slurm, Kubernetes)

Experience running production services, including monitoring and alerting (e.g., Prometheus, Grafana), deployment pipelines, and incident response

Experience building tooling for cluster validation and reliability (accelerator, networking, and storage health checks)

Experience setting up and managing developer tools and third-party services (e.g., cloud storage providers, Docker Hub, Slack, Gmail, Telegraf, experiment trackers)

Excellent debugging and troubleshooting skills across compute, storage, and networking

Strong communication skills and ability to collaborate across technical and non-technical teams

Experience with infrastructure as code (e.g., Ansible, Terraform)

Prior work supporting ML/AI infrastructure, including GPU management and workload optimization

Experience deploying and operating LLM serving stacks (e.g., vLLM, SGLang, Ray)

Experience with multiple accelerator platforms (e.g., NVIDIA CUDA, AMD ROCm, TPUs)

Experience with high-performance networking (InfiniBand, RoCE) and distributed storage

Experience working with cloud platforms such as AWS, Azure, or GCP

Familiarity with Apptainer and with integrating containers into Slurm and Kubernetes