Applied Research Scientist / Engineer

About the role

This is a foundational opportunity to refine, personalize, and build the final capabilities and control interface of Luma’s foundation models and drive real-world value. You’ll sit at the intersection of research, product, and partnerships, helping close the gap between state-of-the-art and production-ready.

What You'll Do

• You will work as a fullstack applied researcher across modeling, data, systems, and evaluation to adapt and deploy models to production.
• Controllability and Features: You will leverage a toolkit spanning SFT, RL, personalization, distillation, control adapters, and more, to develop and maintain model variants purpose-built for user environments and creative partners.
• Personalization: Architect the data engine for rapid adaptation. You will leverage proprietary, vertical-specific datasets to create specialized finetunes and improve future training recipes, ensuring our models rely on data that reflects real-world use cases.
• End-User Quality: You will define and drive end-user quality – setting success metrics, building user-aligned evaluations, and iterating on the model/data/evals loop to meet strict fidelity and reliability targets in specific enterprise verticals.
• Cross-functional Collaboration: Partner closely with Product, Research, and Design to translate creative intent and user feedback into model behavior, intuitive controls, and production-ready capabilities for users and partners.

Who You Are

• Product-Obsessed Researcher/Engineer: You treat end users and partners as collaborators and enjoy solving specific “last mile” problems—not just optimizing public metrics.
• ML Expert: Strong ML fundamentals with deep experience in visual generative models (diffusion/transformers or related architectures). Ideal candidates also have a deep understanding of at least one: fine-tuning, personalization, domain adaptation, data curation, targeted distillation, interpretability, or human-feedback-driven refinement.
• Hands-On Builder: Strong Python and deep learning engineering skills (ideally PyTorch), comfortable moving between research prototypes and production systems. Bonus Points: Contributions to state-of-the-art models in image/video generation. Experience collaborating with creative partners (VFX, animation, film, design tools). Track record building workflows/tools that materially improve iteration speed and evaluation rigor. Familiarity with large-scale training infrastructure and distributed systems (Ray, Slurm, Kubernetes).