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The Customer Success Lead will onboard and support customers in adopting Luma's AI platform, enhancing their workflows, and acting as a liaison between customers and product teams.

As Strategic Customer Success - EMEA, manage enterprise accounts, driving growth and adoption of the platform through relationship building and data insights.

Build the Forward Deployed Creative function: partner with brands and agencies, prototype AI-accelerated production workflows, create high-craft content with Dream Machine, consult on creative strategy, and evangelize generative video while shaping product and partner playbooks.

Embed with customers to define problems, build and ship production systems on Luma's APIs and models, maintain deployed solutions, and surface productizable patterns to R&D and platform teams. Work across the full stack and own projects end-to-end.

Work across modeling, data, systems, and evaluation to make video foundation models expressive, controllable, and personalized. Build adaptation and personalization pipelines, define end-user quality metrics and evaluations, and collaborate with product and design to deploy production-ready model variants for creative partners.

Design, build, and operate large-scale RL post-training systems for multimodal foundation models: distributed training, high-throughput rollout generation, environment and reward infrastructure, evaluation and debugging tooling, and efficiency/stability improvements. Collaborate with researchers to productionize RL methods and run stable RL training across thousands of GPUs.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

Lead sales initiatives for Luma in the UK, develop and execute a sales strategy, engage key decision-makers, and maintain a strong sales pipeline.

The ML Engineer will integrate model architectures, optimize deployment workflows, maintain CI/CD pipelines, and ensure reliability of inference services across large-scale systems.

The role focuses on refining Luma's foundation models for better controllability and personalization while collaborating across research, product, and design teams.