Quantiphi
Architect Platform Engineer
Canada - Remote
Sponsorship not specifiedDetected 16 days ago
GitSnowflakeVector DatabasesAWSGCPAzureCloud PlatformsDockerKubernetesTerraformAnsibleHelmCI/CDJenkinsLinuxPlatform EngineeringMachine LearningData EngineeringData ScienceLLMsRAGAgentic AILLMOpsMLOps
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odds of building a lasting career here
40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- This role is ideal for someone with deep hands-on experience in GPU profiling, distributed training, and high-performance compute environments.
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, 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
- Champion and drive the adoption of Infrastructure as Code (IaC) practices and mindset
- Design, architect, and build self-service, self-healing, synthetic monitoring and alerting platform and tools
Requirements
- 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)
- 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
- 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
Nice to have
- Experience working with FHIR R4, HL7 v2, or SMART on FHIR
- Integration with EHR systems (e.g., Epic)
- Exposure to clinical workflows, CDS Hooks, or patient-facing applications
- Make an impact at one of the world's fastest-growing AI-first digital engineering companies.
- Up-skill and discover your potential as you solve complex challenges in cutting-edge areas of technology alongside passionate, talented colleagues.
- Work where innovation happens - work with disruptive innovators in a research-focused organization with 60+ patents filed across various disciplines.
- Stay ahead of the curve, immerse yourself in breakthrough AI, ML, data, and cloud technologies and gain exposure working with Fortune 500 companies.
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This listing is sourced directly from Quantiphi's careers page and normalized into a canonical job model.