About the RoleThis 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. Your mission is to make our video foundation models more
expressive, controllable, and personalized - solving the "last mile" challenges demanded by top-tier creative workflows.
What You'll DoYou 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).
CompensationThe base pay range for this role is $200,000 - $450,000 per year.
