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 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
Top Skills
Deep Learning
Distributed Systems
Gpu
Machine Learning
Ml Infrastructure
Tpu
Similar Jobs
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
Embed in Research to drive end-to-end delivery of STT/TTS model versions and features. Map dependencies and risks, run cross-functional programs, establish lightweight processes, and communicate status across Research, Product, DataOps, and Engineering to ensure timely launches.
Top Skills:
Audio Data CollectionAudio LabelingData PipelinesDataopsHuman EvaluationLatent Space Models (Lsms)Machine LearningModel EvaluationModel ServingModel TrainingSpeech-To-Text (Stt)Text-To-Speech (Tts)
Artificial Intelligence • Information Technology • Machine Learning • Natural Language Processing • Productivity • Software • Generative AI
Lead a Sales Engineering team to support higher education clients, improve team performance, manage pre-sales processes, and collaborate with sales management to enhance Superhuman's market presence.
Top Skills:
AIProductivity ToolsSaaS
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
The RVP Enterprise Ohio will lead enterprise sales teams selling Identity Security Solutions, managing sales processes, and fostering relationships with clients and partners.
Top Skills:
CybersecurityIdentity SecurityIga Solution SuiteSaaS
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
