Site Reliability Engineer

REALM; Brussel; Teletrabalho; EUR 160 000 - 196 000; Tempo integral

Resumo da oferta

REALM is seeking an SRE who works inside engineering teams running large-scale training and inference. You will diagnose failures, tune jobs, and build automation to keep workloads healthy.

Half the role is deeply technical, half is navigating organization dynamics to avoid friction. You’ll own infrastructure and communicate findings to leadership across Europe in a remote setting.

Qualificações

• Production experience running GPU clusters at scale.
• Strong grasp of distributed training failure modes.
• Solid networking fundamentals across high-speed interconnect fabrics.
• Expert Linux drivers, kernel tuning, container runtimes, hardware-level profiling.
• Kubernetes with GPU workloads in production; HPC scheduler experience.
• Strong engineering skills — you build tools, not just scripts.
• Comfortable briefing a customer’s leadership on infrastructure findings.
• Europe remote.

Responsabilidades

• Embed with the engineering teams running large-scale training and inference, debugging failures alongside them.
• Diagnose failures and tune jobs to prevent repeats; turn learnings into platform improvements.
• Own automation and tooling to raise reliability and throughput of workloads.
• Work effectively inside another team’s organization without friction.
• Communicate findings and risks to leadership and stakeholders.

Conhecimentos

GPU clusters

Distributed training

Networking fundamentals

Linux kernel tuning

Container runtimes

Engineering tools

Kubernetes

Ferramentas

HPC scheduler

Kubernetes

Descrição da oferta de emprego

This is an SRE role that puts you inside the environments you’re responsible for. Not monitoring dashboards from a distance - embedded with the engineering teams running large-scale training and inference, debugging failures alongside them, and owning the infrastructure that keeps their workloads healthy.

The Role

When a large distributed training run breaks, you’re the person who works out why and makes sure it can’t repeat. You’ll tune jobs, diagnose failures, build automation, and turn what you learn in the field into platform improvements.

Half the job is deeply technical. Half is knowing how to work inside someone else’s engineering organisation without friction.

Who they’re looking for

• Production experience running GPU clusters at scale
• Strong grasp of distributed training failure modes - you understand what’s happening at the systems level when a large run stalls
• Solid networking fundamentals across high-speed interconnect fabrics
• Expert Linux - drivers, kernel tuning, container runtimes, hardware-level profiling
• Kubernetes with GPU workloads in production; HPC scheduler experience equally valued
• Strong engineering skills - you build tools, not just scripts
• Comfortable briefing a customer’s leadership on something you found in their infrastructure
• Europe remote
• Up to $200k + meaningful early equity