About Luma
Luma's mission is to build multimodal AI that can generate, understand, and operate in the physical world. We believe real-world physics is the path to general intelligence, and we unite research, product, and go-to-market into one engine to get there. Our models and products are used by millions of creators, developers, and enterprises around the world to expand what's possible with AI-generated imagination.
The Role
Luma is looking for a Commercial and IP Counsel to join our Legal team and help scale the company as we train and ship frontier multimodal models. Reporting directly to the General Counsel, you will be responsible for commercial contracting across the business — API, enterprise, and compute/infrastructure deals — while also owning our intellectual property strategy and the technical IP and data-rights issues that are specific to building generative AI systems.
You'll be expected to get genuinely fluent in how our models are trained and deployed — data sourcing and licensing, model architecture and weights, fine-tuning and distillation, inference infrastructure — so you can spot and structure around the legal issues before they become expensive. You'll work daily with research, applied ML, data, product, and infrastructure teams, and you'll be trusted to make judgment calls in a legal landscape where the case law and regulation are still being written.
What You'll Do
Partner closely with the sales team to draft, negotiate, and close API and enterprise agreements.
Build scalable contracting infrastructure — templates, negotiation playbooks, risk-tiering, and a contract lifecycle process — so the business can move at startup speed as deal volume grows.
Negotiate compute and infrastructure agreements with cloud and GPU providers and agreements with foundation-model or technology partners, including model-hosting, API-reseller, and co-development deals.
Structure and negotiate data licensing and content-partnership agreements for training and fine-tuning datasets— covering scope of use, exclusivity, attribution, and downstream rights.
Advise research and engineering on IP ownership for training methods, model weights, checkpoints, and derivative/fine-tuned models, including questions raised by open-weight releases and third-party model integration.
Advise on open-source and third-party license compliance for code, model weights, and datasets used in research and production (e.g., copyleft obligations, model license restrictions, attribution requirements).
Advise on copyright and data-rights issues in sourcing, licensing, and using training and fine-tuning data, including scraped, licensed, user-generated, and synthetic data.
Work with internal stakeholders on output-side IP risk: substantial-similarity and infringement exposure in generated video/image/3D content, style-mimicry claims, and takedown/DMCA processes.
Advise on content provenance and authenticity questions as they intersect with commercial terms and emerging regulations.
Review and advise on Customer DPAs and privacy questionnaires.
About You
J.D. and active membership in at least one U.S. state bar.
5+ years of experience spanning law firm and in-house work, with substantial time on technology commercial transactions and IP.
Proven track record negotiating SaaS/API agreements, data licensing deals, and cloud/compute or infrastructure contracts with minimal supervision.
Working technical fluency with how generative AI models are built and deployed — training data pipelines, fine-tuning/distillation, model weights and checkpoints, inference serving — sufficient to negotiate terms and issue-spot without translation from engineers.
Substantive experience with the IP issues specific to AI: copyright and training-data rights, output ownership and infringement risk, open-source/open-weight model licensing, and patentability of ML techniques.
Familiarity with the emerging AI regulatory landscape (e.g., EU AI Act, U.S. state AI laws, content-provenance/disclosure rules) and how it intersects with commercial and IP terms.
Excellent judgment on balancing legal risk against the pace of a frontier research company — comfortable operating without settled precedent.
A builder's mindset: energized by creating process and infrastructure where none exists yet, not just executing an existing playbook.
Clear, direct communicator who can explain complex legal and technical tradeoffs to researchers, engineers, and executives alike.
Bonus: prior in-house experience at a foundation model lab, AI infrastructure company, or developer platform; technical background (CS/EE) or fluency reading ML papers.