Tech Architect

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Create and implement scalable infrastructure for LLM and GenAI applications within multi-GPU frameworks.

• Conduct GPU profiling, benchmarking, and enhance performance for distributed training tasks.

• Oversee and schedule compute-heavy jobs utilizing Slurm-based clusters and OpenShift/Kubernetes setups.

• Activate and optimize the NVIDIA GPU stack, which includes CUDA, cuDNN, NCCL, Triton, and RAPIDS.

• Collaborate with diverse teams to deploy models in both research and production settings.

• Develop and maintain GenAI pipelines, encompassing fine-tuning, RAG, multi-modal inferencing, and LLMOps.

• Create reusable infrastructure templates utilizing Terraform and Helm.

• Contribute to internal innovation through proofs of concept and workshops.

• Assist in client-facing delivery engagements.

• Collaborate with data science, MLOps, and application teams to establish production-ready foundations for GenAI platforms.

⛳️ Requirements

• Over 10 years of relevant experience.

• Extensive experience with Slurm and distributed training environments.

• Practical expertise in Red Hat OpenShift and/or Kubernetes.

• In-depth understanding of the NVIDIA GPU ecosystem, including CUDA, cuDNN, NCCL, Nsight, and Triton/TensorRT.

• Solid foundation in Linux systems, performance tuning, and multi-GPU optimization.

• Experience in deploying GenAI workloads, such as LLM fine-tuning, RAG pipelines, and multi-modal systems.

• Familiarity with Infrastructure-as-Code tools like Terraform and Ansible.

• Experience with cloud GPU platforms, 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 roles and collaborating with AI solution teams.

• Experience in the healthcare sector is a plus: FHIR R4, HL7 v2, SMART on FHIR, EHR integration, HIPAA compliance, clinical workflows, CDS Hooks, patient-facing applications, clinical decision support systems, or healthcare interoperability solutions.

🏝️ Benefits

• Opportunities for upskilling and professional development.

• Exposure to leading-edge AI, ML, data, and cloud technologies.

• Chance to work with Fortune 500 companies.

• Employment in a research-driven organization with over 60 patents filed.

• Collaboration with dedicated and talented colleagues.

• Career advancement in a rapidly growing AI-focused digital engineering firm.