Platform Support Engineer

Required Qualifications

Infrastructure & Systems

• Strong software engineering and systems troubleshooting background
• Experience with Kubernetes and containerized environments
• Linux systems knowledge, including networking, storage, process management, and performance tuning
• Experience with cloud infrastructure and distributed systems
• Experience with observability and debugging tools such as Prometheus, Grafana, or OpenTelemetry

ML Infrastructure Experience

• Hands on experience operating machine learning workloads in production or research environments
• Experience with distributed ML systems and tooling such as PyTorch, CUDA, or NCCL
• Familiarity with GPU infrastructure and orchestration
• Experience troubleshooting performance, reliability, or scaling issues in ML infrastructure
• Understanding of the operational challenges involved in running ML systems at scale

Collaboration

• Strong communication skills and ability to work directly with highly technical customers and engineering teams
• Comfortable operating in fast moving, highly ambiguous environments
• Enjoys solving complex technical problems collaboratively

Nice-to-Haves

• Experience with large scale model training or distributed inference systems
• Familiarity with Ray, Kubeflow, Slurm, or similar distributed scheduling platforms
• Experience with InfiniBand, RDMA, or high-performance networking
• Experience operating bare metal infrastructure
• Familiarity with storage systems commonly used in ML environments
• Experience working at an AI infrastructure, cloud, MLOps, or developer tooling company
• Contributions to platform engineering, developer infrastructure, or operational tooling projects
• Experience writing automation, tooling, or scripts in Python or similar languages