AI Platform Engineer for ML Infra & Scale (Hybrid)

Lightningai; Greater London; Hybride; GBP 75 000 - 95 000; Plein temps

Avantages offerts par ce poste

Comprehensive Health Coverage

Meaningful Equity

Retirement Savings

Flexible Time Off

Company-Wide Winter Break

Paid Parental & Family Leave

Professional Development

Wellness Benefits

Sabbatical Program

Flexible Work

In-Office Meals

Résumé du poste

Lightning AI is hiring AI Platform Support Engineers for its EMEA Customer Experience team, supporting ML engineers on large-scale training and inference workloads across cloud, Kubernetes, and GPU platforms in production. The role operates in London with a hybrid in-office requirement and two shifts (9AM–7PM CET/CEST).

You’ll diagnose failures in distributed systems, improve reliability, and guide customers through complex environments.

Qualifications

• Strong software engineering and systems troubleshooting background.
• Experience with Kubernetes and containerized environments.
• Linux systems knowledge including networking, storage, and performance tuning.
• Experience with cloud infrastructure and distributed systems.
• Familiarity with observability and debugging tools (Prometheus, Grafana, OpenTelemetry).
• Hands on experience operating ML workloads in production or research environments.

Responsabilités

• Partner directly with customer engineering teams running training and inference workloads in production.
• Help diagnose and resolve complex distributed systems and ML infrastructure issues.
• Act as a technical advisor during high impact incidents and platform degradation events.
• Translate infrastructure issues into actionable guidance for ML engineers.
• Build credibility with customers through strong technical reasoning and clear communication.

Connaissances

Kubernetes

Linux

Distributed systems

Python

Observability

Outils

Prometheus

Grafana

OpenTelemetry

PyTorch

CUDA

NCCL

Ray

Kubeflow

Slurm

InfiniBand

Description du poste

Lightning AI is hiring AI Platform Support Engineers for its EMEA Customer Experience team, supporting ML engineers on large-scale training and inference workloads across cloud, Kubernetes, and GPU platforms in production. The role operates in London with a hybrid in-office requirement and two shifts (9AM–7PM CET/CEST).

You’ll diagnose failures in distributed systems, improve reliability, and guide customers through complex environments.