AI Platform Support Engineer (EMEA)

Location: Hybrid from the London office, with at least 2 in-office days per week. EMEA shifts run from 9AM–7PM CET/CEST on either Saturday–Tuesday or Thursday–Sunday. Occasional team and company offsites are required. Visa sponsorship is not available.

Annual base salary: £75,000–£95,000 GBP, plus discretionary bonus, equity, and benefits.

Company

hirify.global builds an end-to-end platform for developing, training, and deploying AI systems, combining developer-first software with large-scale AI compute.

What you will do

• Partner directly with customer ML engineering teams running production training and inference workloads.
• Diagnose distributed systems and ML infrastructure issues involving Kubernetes, GPU allocation, networking, storage, and inference serving.
• Troubleshoot PyTorch, CUDA, NCCL, containerized workloads, and multi-node GPU systems.
• Analyze logs, metrics, traces, and system behavior to identify root causes and performance bottlenecks.
• Drive reliability improvements through post-incident reviews, observability enhancements, documentation, runbooks, and automation.
• Collaborate with infrastructure, networking, and platform engineering teams to improve customer troubleshooting workflows.

Requirements

• Strong software engineering and systems troubleshooting experience.
• Experience with Kubernetes, containers, cloud infrastructure, and distributed systems.
• Linux expertise covering networking, storage, process management, and performance tuning.
• Experience operating and troubleshooting production or research machine learning workloads, including distributed ML systems such as PyTorch, CUDA, or NCCL.
• Experience with GPU infrastructure, orchestration, observability, and debugging tools such as Prometheus, Grafana, or OpenTelemetry.
• Strong communication skills and the ability to work directly with technical customers and engineering teams.

Nice to have

• Experience with large-scale model training, distributed inference, Ray, Kubeflow, Slurm, or similar scheduling platforms.
• Knowledge of InfiniBand, RDMA, high-performance networking, bare-metal infrastructure, or ML storage systems.
• Experience at an AI infrastructure, cloud, MLOps, or developer tooling company.
• Contributions to platform engineering, developer infrastructure, or operational tooling projects.
• Experience writing automation, tooling, or scripts in Python or similar languages.

Culture & Benefits

• Fast-moving environment focused on ownership, open communication, continuous improvement, and long-term scalable systems.
• Medical, dental, and vision coverage for employees and eligible dependents.
• Equity, retirement savings support, unlimited PTO, company holidays, and a two-week winter break.
• Paid parental and family leave, professional development allowance, wellness benefits, and work-from-home stipends.
• Four weeks of paid sabbatical after four years of service, flexible schedules, and complimentary office meals.