Senior Platform Engineer

Job summary

Qua*** is seeking a Senior Platform Engineer to design, optimize, and scale infrastructure for GenAI and LLM workloads. The role involves collaborating with cross-functional teams to deploy AI solutions and requires deep hands-on experience in GPU profiling and distributed training environments.

Qualifications

• Strong experience with Slurm and distributed training environments
• Hands-on expertise with Red Hat OpenShift and/or Kubernetes
• Deep knowledge of the NVIDIA GPU ecosystem (CUDA, cuDNN, NCCL, Nsight, Triton/TensorRT)
• Strong foundation in Linux systems, performance tuning, and multi-GPU optimization
• Experience deploying GenAI workloads (LLM fine-tuning, RAG pipelines, multi-modal systems)
• Familiarity with Infrastructure-as-Code tools (Terraform, Ansible)
• Experience with cloud GPU environments (GCP, Azure, AWS, OCI) and/or on-prem GPU clusters

Responsibilities

• Design and implement scalable infrastructure for LLM and GenAI workloads across multi-GPU environments
• Perform GPU profiling, benchmarking, and performance optimization for distributed training workloads
• Manage and schedule compute-intensive jobs using Slurm-based clusters and OpenShift/Kubernetes environments
• Enable and optimize the NVIDIA GPU stack (CUDA, cuDNN, NCCL, Triton, RAPIDS)
• Collaborate with cross-functional teams to deploy models in research and production environments
• Build and support GenAI pipelines (fine-tuning, RAG, multi-modal inferencing, LLMOps)
• Develop reusable infrastructure templates using Terraform and Helm
• Contribute to internal innovation and support client-facing delivery engagements

Skills

Relocation