Senior Platform Engineer

🕒 April 14

🏄 California – Remote

🏄 California – Remote

⏰ Full Time

🟠 Senior

🏗️ Platform Engineer

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Quantiphi

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2013

💼 Consulting

🏥 Healthcare

📦 Logistics

💰 Series A on 2019-12

Consulting • Healthcare • Logistics

Quantiphi is a leading AI-first digital engineering company that leverages a decade of industry expertise to empower businesses through scalable, secure, and adaptable AI solutions. By integrating cutting-edge technology with real-world applications, Quantiphi transforms organizations across various sectors including healthcare, finance, education, and retail. Their services span AI applications, data analytics, cloud infrastructure modernization, and custom AI implementations. Quantiphi partners with technology giants like AWS, Google Cloud, NVIDIA, and others to drive AI adoption and deliver transformational opportunities for enterprises.

📋 Description

• 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, etc.) • 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 tools like Terraform and Helm • Contribute to internal innovation (PoCs, workshops) and support client-facing delivery engagements

🎯 Requirements

• 8+ years of experience • 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

🏖️ Benefits

• Health insurance • Various career growth opportunities • Flexible working hours • Paid time off

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