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Forward Deployed Engineers at Luma build systems based on customer workflows, defining problems and delivering production solutions using Luma's models and APIs.

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.

As a Software Engineer in Reliability, you'll architect and manage multi-cloud GPU infrastructure, ensuring performance, security, and scale while debugging complex hardware/software issues.

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.

Seeking a Research Scientist/Engineer to design and optimize distributed training systems for large-scale multimodal AI models using thousands of GPUs.

The Research Engineer will design scalable evaluation systems for multimodal generative AI models, integrating metrics and automated pipelines for model assessment and improvement.

Lead and hands-on build Luma's inference serving platform: architect scheduling, routing, autoscaling, and observability across thousands of GPUs; operate and optimize heterogeneous fleets; ship new model architectures from research to production; own SLOs, cost, incidents, and team hiring/mentorship.

The role involves using AI tools to rapidly develop software, working across product and engineering teams, and owning software projects end-to-end.

This role requires shaping technical direction, leveraging AI tools for production systems, and making crucial decisions to align product intent with engineering realities.