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Senior AI Compute Infrastructure Engineer
Kraken Digital Asset ExchangeSenior AI Compute Infrastructure Engineer building GPU infrastructure at Kraken. Collaborating with AI researchers to optimize compute resources for AI workloads.
Tech Stack
Tools & technologiesCloudKubernetesLinuxPython
About the role
Key responsibilities & impact- Own and operate GPU and accelerator clusters
- Design infrastructure that enables Kraken teams to run models locally
- Build and improve scheduling, orchestration, placement, quota management
- Optimize inference pipelines for latency, throughput, reliability
- Partner with ML engineers to remove bottlenecks in workflows
- Build observability for GPU utilization and capacity pressure
- Drive reliability, incident response, and post-incident improvements
- Evaluate and integrate new hardware and cloud resources
- Contribute to long-term architecture decisions
Requirements
What you’ll need- 5+ years of infrastructure engineering experience
- Hands-on experience operating GPU clusters or accelerator-backed infrastructure
- Strong systems engineering fundamentals across Linux, networking, storage, containers, Kubernetes
- Experience with ML serving frameworks such as vLLM, Triton Inference Server, TensorRT
- Proficiency in Python for infrastructure automation
- Track record of optimizing compute costs
- Experience building observable systems with useful metrics, logs, traces, dashboards, alerts
Benefits
Comp & perks- Building the Future of Crypto
- Kraken culture and values
- Commitment to industry-leading security and crypto education
- World-class client support through products
- Flexible work arrangements
ATS Keywords
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Hard Skills & Tools
GPU clustersaccelerator-backed infrastructureLinuxnetworkingstoragecontainersKubernetesvLLMTriton Inference ServerTensorRT
Soft Skills
problem-solvingcollaborationincident responsereliability engineering