Senior AI Compute Infrastructure Engineer

About the role

Kraken, a leading crypto platform under Payward, is building a dedicated AI Compute and Infrastructure team. As a Senior AI Compute Infrastructure Engineer you will design, operate, and scale GPU and accelerator clusters that power model training, inference, and experimentation across the exchange.

Key responsibilities

• Own and operate GPU/accelerator clusters, including drivers, runtimes, kernels, device plugins, and node configuration.
• Design scheduling, orchestration, placement, quota management, and utilization systems for heterogeneous accelerator environments.
• Optimize inference pipelines for latency, throughput, reliability, memory efficiency, and cost using frameworks such as vLLM, Triton Inference Server, and TensorRT.
• Partner with ML researchers and platform engineers to remove bottlenecks in training, evaluation, batch and online inference, and production debugging.
• Build observability for GPU utilization, memory pressure, queue depth, token throughput, request latency, failed workloads, capacity pressure, and spend.
• Drive reliability through incident response, alerting, runbooks, and post‑incident improvements for always‑on AI compute.

Required profile

• Senior‑level experience designing and operating large‑scale GPU or accelerator infrastructure.
• Proven ability to work with cross‑functional AI/ML, security, and product teams.
• Strong focus on performance, cost efficiency, and production‑grade reliability.

Required skills

• GPU and accelerator hardware management
• Driver and runtime configuration
• Kernel and device plugin development
• Scheduling and orchestration systems
• vLLM, Triton Inference Server, TensorRT
• Observability and monitoring of compute resources