5 days ago
Responsibilities
- Design and implement scalable multi-GPU infrastructure for LLM and GenAI workloads.
- Profile, benchmark, and optimize GPU and distributed-training performance.
- Manage compute-intensive jobs using Slurm-based clusters and OpenShift/Kubernetes environments.
- Enable and optimize the NVIDIA GPU stack, including CUDA, cuDNN, NCCL, Nsight, Triton, TensorRT, and RAPIDS.
- Collaborate with data science, MLOps, application, and AI solution teams to deploy models in research and production environments.
- Build and support GenAI pipelines for fine-tuning, RAG, multimodal inference, and LLMOps.
- Develop reusable infrastructure templates with Terraform, Helm, and Ansible.
- Contribute to proofs of concept and workshops and support client-facing delivery engagements.
Requirements
- 10+ years of experience in platform engineering, infrastructure, or related technical work.
- 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, and TensorRT.
- Strong foundation in Linux systems, performance tuning, and multi-GPU optimization.
- Experience deploying GenAI workloads such as LLM fine-tuning, RAG pipelines, and multimodal systems.
- Experience with infrastructure-as-code tools including Terraform and Ansible.
- Experience with cloud GPU environments such as GCP, Azure, AWS, or OCI and/or on-premises GPU clusters.
- Preferred experience with NVIDIA NIMs, DGX systems, GPU-accelerated containers, LLMOps frameworks, MLOps integration, vector databases, and retrieval systems.
- Client-facing collaboration experience with AI solution teams is preferred.
- Healthcare experience with FHIR R4, HL7 v2, SMART on FHIR, Epic, HIPAA, CDS Hooks, clinical workflows, or healthcare interoperability is preferred.
Benefits
- Full-time remote work in Canada or the US.
- Opportunities to work on cutting-edge AI, ML, data, cloud, and GenAI technologies with Fortune 500 clients.
- Upskilling and professional growth in a research-focused organization.
- Exposure to innovation initiatives and a company with 60+ filed patents.
- Collaborative work with an international team at a Great Place to Work-certified company.
Tech Stack
Categories
About Quantiphi
Quantiphi is an AI-first digital engineering and consulting firm that designs and implements machine learning, data, and cloud solutions for large enterprises across industries. Its teams build production systems—such as generative AI applications, computer vision, and predictive analytics—primarily on Google Cloud and other hyperscalers, delivered as professional services and managed solutions. Founded in 2013 and headquartered in Marlborough, Massachusetts, the company is privately held and a Google Cloud partner.