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 • Cloud • Computer Vision • Hardware • Internet of Things • Software
Design, develop, debug, and test cloud-connected firmware features (C/C++ and Go). Support and scale IoT device fleet, build observability and rollout metrics, triage customer/QA issues, and collaborate cross-functionally to deliver production-ready firmware.
Top Skills:
BuildkiteC++CanCan-UtilsDatabricksGoGraphQLLinuxLinux DriversLteSocUsbWifi
eCommerce • Fintech • Hardware • Payments • Software • Financial Services
Develop and manage Square’s always-on B2B content engine across social, thought leadership, customer stories, partner content, and industry narratives. Build content calendars, formats, briefs, campaigns, and AI-assisted workflows; coordinate cross-functional teams and external partners; oversee production through launch; and analyze performance to optimize messaging, formats, and distribution.
Top Skills:
Ai ToolsLinkedInSocial AnalyticsSocial Media Platforms
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Develop and manage Square’s always-on B2B content engine across social, thought leadership, customer stories, partner content, and industry narratives. Build content calendars, formats, briefs, campaigns, and AI-assisted workflows; collaborate with marketing, sales, creative, communications, and external partners; manage production through launch; and use performance insights to optimize content and distribution.
Top Skills:
Ai ToolsLinkedInSocial Media Platforms
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories


.png)
