Member of Technical Staff, AI Infrastructure Team (AI)

Location: Helsinki, Finland or London, UK. Hybrid work from the Helsinki or London office three days per week.

Company

hirify.global is a full-stack AI cloud company that installs, operates, and optimizes compute infrastructure for AI model training and inference.

What you will do

• Improve networking and communication layers for large-scale LLM training workloads.
• Optimize collective communication across distributed GPU clusters to improve throughput, utilization, and reliability.
• Debug networking-stack bottlenecks and build tooling for benchmarking, profiling, and regression testing.
• Collaborate with training, infrastructure, hardware, and networking teams to improve workload scaling across clusters.
• Build tools and dashboards for identifying NCCL bottlenecks, slow ranks, communication tail latency, and training network health.
• Implement fault-tolerance mechanisms that reduce cluster idle time and improve training efficiency.

Requirements

• Experience with distributed systems, networking, or large-scale ML training infrastructure.
• Experience with communication libraries such as NCCL, MPI, NVSHMEM, or similar technologies.
• Experience with profiling and debugging tools such as Nsight Systems, NCCL logs, PyTorch Profiler, or perf.
• Strong systems thinking and ability to analyze performance bottlenecks across distributed environments.
• Ability to independently define and drive technical projects.
• Curiosity about low-level systems, networking, and large-scale AI infrastructure.

Culture & Benefits

• Full-time, permanent employment.
• Highly collaborative, research-adjacent work across technical teams.
• Opportunity to contribute while the AI cloud infrastructure is still being built.

Hiring process

• Submit an application through the Careers page; applications sent by email are not accepted.
• Hiring proceeds without an artificial deadline and moves forward when a suitable candidate is found.