Role Overview:

We are looking for a highly skilled Senior Platform Engineer to design, optimize, and scale infrastructure for GenAI and LLM workloads. This role is ideal for someone with deep hands-on experience in GPU profiling, distributed training, and high-performance compute environments.

You’ll play a key role in building out GenAI platform foundations, supporting production-grade deployments, and partnering closely with data science, MLOps, and application teams to bring cutting-edge AI solutions to life.

Key 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

Basic 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)
- Solid 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

Other Qualifications (OQs):

- 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 (Nice to Have):

- Experience working with FHIR R4, HL7 v2, or SMART on FHIR
- Integration with EHR systems (e.g., Epic)
- Understanding of HIPAA compliance and healthcare data privacy
- Exposure to clinical workflows, CDS Hooks, or patient-facing applications
- Experience building clinical decision support systems or healthcare interoperability solutions

What’s in it for YOU at Quantiphi:

- Make an impact at one of the world’s fastest-growing AI-first digital engineering companies.
- Upskill 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.

📌 GCP Platform Engineer (Canada)
🏢 Quantiphi
📍 Canada