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.
About Luma AI
Luma's mission is to build multimodal AI to expand human imagination and capabilities. We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable, and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.
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. 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 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.
- 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).
The base pay range for this role is $200,000 – $450,000 per year.
About LumaLuma’s mission is to build unified general intelligence that can generate, understand, and operate in the physical world.
We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.
Similar Jobs
Artificial Intelligence • Fintech • Software
Outbound-focused sales role responsible for prospecting finance and accounting decision-makers, qualifying leads, scheduling demos, documenting activities in Salesforce, and collaborating with Account Executives and Marketing to meet activity and conversion targets.
Top Skills:
SaaSSalesforce
Artificial Intelligence • Fintech • Software
Drive outbound prospecting to finance and accounting leaders, qualify leads, schedule demos, and document activity in Salesforce. Use audit/accounting background to identify client pain points and collaborate with Account Executives, Marketing, and Sales Management to convert prospects.
Top Skills:
Salesforce
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Own vision, strategy, and roadmap for cost-optimization and energy-management products for fleets. Translate telematics and operational data into customer-facing features, run discovery, prototype MVPs, define success metrics, and ship end-to-end with cross-functional teams.
Top Skills:
AIData ScienceMachine LearningTelematics
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
