Senior Platform Engineer

🕒 August 16

🏖️ New Jersey, Massachusetts – Remote

🏖️ New Jersey – Remote 🍂 Massachusetts – 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, including CUDA, cuDNN, NCCL, Triton, and RAPIDS • Collaborate with cross-functional teams to deploy models in research and production environments • Build and support GenAI pipelines, including fine-tuning, RAG, multimodal inferencing, and LLMOps • Develop reusable infrastructure templates using Terraform and Helm • Contribute to internal innovation through proofs of concept and workshops • Support client-facing delivery engagements

🎯 Requirements

• 5+ 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, including CUDA, cuDNN, NCCL, Nsight, Triton/TensorRT • Strong foundation in Linux systems, performance tuning, and multi-GPU optimization • Experience deploying GenAI workloads, including LLM fine-tuning, RAG pipelines, and multimodal systems • Familiarity with Infrastructure-as-Code tools such as Terraform and Ansible • Experience with cloud GPU environments including GCP, Azure, AWS, OCI and/or on-premises GPU clusters • Experience with NVIDIA NIMs, DGX systems, or GPU-accelerated containers • Knowledge of LLMOps frameworks and MLOps integration • Familiarity with vector databases and retrieval systems for RAG architectures • Comfortable working in client-facing environments and collaborating with AI solution teams • Healthcare domain experience is nice to have, including FHIR R4, HL7 v2, SMART on FHIR, EHR integrations, HIPAA, CDS Hooks, clinical workflows, and clinical decision support systems

🏖️ Benefits

• Upskilling and professional development opportunities • Exposure to AI, ML, data, and cloud technologies • Opportunity to work with Fortune 500 companies • Research-focused organization with 60+ patents filed • Collaboration with talented colleagues around the globe • Hybrid work culture