AI HPC Infrastructure Engineer

Locations US-MA-Boston Category Information Technology Overview ------------

Analysis Group is one of the largest international economics consulting firms, with more than 1,500 professionals across 15 offices in North America, Europe, and Asia. Since 1981, we have provided expertise in economics, finance, health care analytics, and strategy to top law firms, Fortune Global 500 companies, and government agencies worldwide. Our internal experts, together with our network of affiliated experts from academia, industry, and government, offer our clients exceptional breadth and depth of expertise.

The AI HPC Infrastructure Engineer owns the operation, performance, and growth of a hybrid high-performance computing (HPC) and AI/GPU infrastructure environment. The engineer maintains the Linux-based clustered computing platform that supports both traditional HPC/analytical workloads and large-scale AI/ML training and inference, ensuring systems run efficiently, GPUs and other accelerators are current and well-utilized, and operations are monitored, documented, and reported — including change management and performance statistics — across both domains.

Essential Job Functions and Responsibilities

* Maintain, tune, and manage the analytical and AI computing environment for researchers and data scientists, including Posit Workbench (RStudio Server Pro) environments. * Optimize systems and infrastructure performance using parallelization technologies (MPI, OpenMP) and distributed/multi-GPU training strategies (e.g., PyTorch Distributed, Horovod, DeepSpeed). * Design, deploy, and maintain GPU-accelerated compute infrastructure for large-scale model training and inference. * Manage GPU scheduling, multi-tenancy, and utilization across SLURM and/or Kubernetes-based environments. * Administer the NVIDIA software stack — drivers, CUDA, cuDNN, NCCL — and coordinate firmware and health monitoring across GPU fleets. * Tune and optimize LLM training