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Jobs / Lightningai

AI Platform Support Engineer (EMEA)

Lightningai·Londonmid

In short

  • →Ingeniero de soporte técnico especializado en plataformas de IA para equipos de ML en producción.
  • →Diagnostico de fallos en Kubernetes, GPUs, PyTorch distribuido y rendimiento de inferencia.
  • →Trabajas como socio técnico con clientes EMEA en entornos de nube a gran escala, no solo resolviendo tickets.

Fluent technical English required for customer and team communication.

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The questions they'll ask you

1. ¿Cómo diagnosticarías una subida repentina en la latencia de inferencia en un clúster Kubernetes con GPU?

2. Describe un caso de fallo distribuido en PyTorch DDP que hayas resuelto; qué herramientas usaste.

3. ¿Qué cambios harías en un pod con GPU para reducir bottleneck de memoria durante entrenamiento?

🔒 +7 more questions

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💵 USD · Remote · No visa

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What they ask for

  • ✓Experiencia con Kubernetes y arquitecturas de clusters distribuidos.
  • ✓Conocimiento avanzado de PyTorch y entrenamiento distribuido (DataParallel, DDP).
  • ✓Experiencia diagnóstico de problemas de GPU (CUDA, driver, memoria, rendimiento).
  • ✓Capacidad para analizar logs y métricas de rendimiento (inference latency, throttling).
  • ✓Familiaridad con infraestructura de nube (AWS, GCP, Azure) y redes de alta disponibilidad.
  • ✓Buena comunicación técnica en inglés y capacidad para explicar problemas complejos.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PyTorch LightningKubernetesDockerGPU orchestrationCUDAAWSGCPAzurePrometheusGrafana

Who should you write to at Lightningai?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

Who We Are Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction. Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in. We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute. The Way We Work The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice: • Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping. • Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through. • Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together. • Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work. • Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most. • Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact. What We’re Looking For Lightning AI is looking to hire AI Platform Support Engineers to join our EMEA Customer Experience team, supporting ML engineers running large-scale training and inference workloads across cloud infrastructure, Kubernetes, and GPU platforms in production environments. This role is not a ticket router or traditional support engineer. You are a technical partner to ML teams - helping diagnose failures, improve reliability, and guide customers through complex distributed systems problems.The problems range from Kubernetes scheduling and GPU orchestration to distributed PyTorch failures, inference latency, networking bottlenecks, storage performance, and platform reliability. You’ll gain exposure to a wide variety of real world AI workloads across industries and help shape the infrastructure powering the next generation of ML applications. We are currently hiring for the following shift (9AM–7PM CET/CEST): <li data-section-id="1ux398t" data-star

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