SRE | Foundation Models

2 days ago

London, Greater London, United Kingdom Luma AI Full time £60,000 - £120,000 per year
The Opportunity Luma AI is training the multimodal models that will define the next era of intelligence. Unlike other software companies, our product roadmap is driven by research breakthroughs. This requires a symbiotic relationship between our infrastructure engineers and our research scientists. We provide the massive compute resources necessary to compete at the top tier of AI, with a team structure that ensures you are in the room where the models are designed.
Where You Come In You will build the platform that enables scientific discovery. Your work will directly accelerate the velocity of our research team, ensuring they have a stable, performant, and scalable environment to train and test the next generation of Omni models. You will translate the complex requirements of large-scale ML workloads into robust infrastructure reality.
What You Will BuildResearch Platforms: Design and maintain the scheduling and orchestration systems that allow researchers to launch and manage massive training jobs with ease.Observability for Intelligence: Implement deep observability stacks that provide transparency into cluster health, allowing us to predict and prevent interruptions to critical training runs.Scalable Inference: Architect the production systems that serve our models to the world, balancing the high availability required for consumer products with the massive compute intensity of generative AI.
The Profile We Are Looking ForService Orientation: You understand that reliable infrastructure is the enabler of innovation, and you care deeply about the developer experience of the researchers you support.Operational Excellence: You have a track record of maintaining high availability in complex, distributed environments, using automation to reduce toil.ML Infrastructure Fluency: You are familiar with the unique demands of AI workloads, including the management of GPU resources and the intricacies of distributed training.

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