Manage technical programs for generative AI video models, translating research into milestones, coordinating teams, and ensuring successful execution across all phases.
Technical Program Manager - Multimodal
About Luma
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
We’re looking for a Technical Program Manager to partner closely with researchers and engineers building state-of-the-art generative AI video models. In this role, you’ll help turn cutting-edge research into scalable, reliable systems by driving execution across research, infrastructure, and product engineering.
You will operate at the intersection of research, systems, and delivery, helping teams plan, prioritize, and execute complex technical programs while preserving the exploratory nature of research.
What You’ll Do
- Partner with research scientists, ML engineers, and infrastructure teams to plan and deliver programs for generative video model development
- Translate research goals into clear technical milestones, timelines, and dependencies
- Drive execution across the full lifecycle: experimentation → training → evaluation → scaling → deployment
- Coordinate cross-functional efforts spanning: Model training and evaluation, Data pipelines and curation, Compute planning (GPU/TPU usage, scheduling, cost awareness), Inference optimization and deployment
- Create lightweight but effective program artifacts (roadmaps, risk registers, decision logs)
- Identify risks early (technical, resourcing, compute, data) and proactively drive mitigations
- Improve operational rigor without slowing down research velocity
- Act as a connective tissue between research, product, and platform teams
- Help define and evolve best practices for running large-scale AI research programs
What We’re Looking For
Required Qualifications:
- 5+ years of experience in Technical Program Management, Engineering Program Management, or similar role
- Strong technical background with the ability to engage deeply with: Machine learning concepts (especially deep learning), Large-scale training and experimentation workflows, Distributed systems or ML infrastructure
- Experience working directly with researchers or research-adjacent teams
- Proven ability to manage ambiguous, fast-evolving technical programs
- Excellent communication skills — able to align highly technical stakeholders
Preferred Qualifications:
- Experience with generative models, especially video, vision, or multimodal systems
- Familiarity with: Model training at scale (multi-node, multi-GPU), Data versioning, experiment tracking, and evaluation frameworks, ML deployment and inference optimization
- Background in computer science, engineering, or a related technical field
- Experience in AI-first or research-driven organizations
How You’ll Be Successful
- You bring structure without rigidity to research-driven teams
- You’re comfortable operating in uncertainty and helping others navigate it
- You can dive deep technically, but also zoom out to align teams on priorities
- You care deeply about execution quality, but respect the iterative nature of research
Why Join Us
- Work alongside leading researchers pushing the frontier of generative AI video
- Influence how cutting-edge research becomes real-world technology
- Help shape the operational foundations of next-generation AI systems
- Competitive compensation, meaningful equity, and strong benefits
About Luma
Luma’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.
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