Job description

ABOUT WORLD LABS World Labs worldlabs.ai is a frontier AI research and product company advancing spatial intelligence, the next frontier beyond large language models. Co-founded by Dr. Fei-Fei Li profiles.stanford.edu, Justin Johnson linkedin.com and Ben Mildenhall linkedin.com, the company is pioneering world models that perceive, generate, reason, and interact with virtual and physical worlds. The company’s flagship product, Marble marble.worldlabs.ai, transforms text, images, and video into fully navigable 3D worlds, unlocking applications across gaming, film, architecture, robotics, and immersive digital experiences. Backed by leading investors and with over $1B raised, World Labs is assembling a world-class team at the intersection of AI research and real-world deployment. ROLE OVERVIEW We are looking for a talented Research Scientist with a strong background in generative modeling, particularly diffusion models, to join our modeling team. This role is ideal for candidates with deep expertise in diffusion models applied to images, videos, or 3D assets and scenes. While not required, experience in one or more of the following areas is a strong plus: - Large-scale model training - Data curation for pre-training or post-training - Tokenizers and VAEs for image, video, or 3D data - Long-context architectures - 3D vision You will collaborate closely with researchers, engineers, and product teams to bring advanced 3D modeling and machine learning techniques into real-world applications, ensuring that our technology remains at the forefront of visual innovation. This role involves significant hands-on research and engineering work, driving projects from conceptualization through to production deployment. WHAT YOU WILL DO - Design, implement, and train large-scale diffusion models for generating 3D worlds - Develop and experiment with large-scale diffusion models to add novel control signals, adapt to target aesthetic preferences, or distill for efficient inference - Collaborate closely with research and product teams to understand and translate product requirements into effective technical roadmaps. - Contribute hands-on to all stages of model development including data curation, experimentation, evaluation, and deployment. - Continuously explore and integrate cutting-edge research in diffusion and generative AI more broadly - Act as a key technical resource within the team, mentoring colleagues, and driving best practices in generative modeling and ML engineering KEY QUALIFICATIONS - 3+ years of experience in generative modeling or applied ML roles, ideally at a startup or other fast-paced research environment - Extensive experience with machine learning frameworks such as PyTorch or TensorFlow, especially in the context of diffusion models and other generative models - Deep expertise in at least one area of generative modeling: pre-training, post-training, diffusion distillation, fine-tuning with new conditioning signals, etc for diffusion models - Strong history of publications or open-source contributions involving large-scale diffusion models - Strong coding proficiency in Python and experience with GPU-accelerated computing. - Ability to engage effectively with researchers and cross-functional teams, clearly translating complex technical ideas into actionable tasks and outcomes. - Comfortable operating within a dynamic startup environment with high levels of ambiguity, ownership, and innovation. PREFERRED QUALIFICATIONS - Contributions to open-source projects in the fields of computer vision, graphics, or ML. - Familiarity with large-scale training infrastructure (e.g., multi-node GPU clusters, distributed training environments). - Experience integrating machine learning models into production environments. - Led or been involved with the development or training of large-scale, state-of-the-art generative models WHO YOU ARE - Fearless Innovator: We need people who thrive on challenges and aren't afraid to tackle the impossible. - Resilient Builder: Impacting Large World Models isn't a sprint; it's a marathon with hurdles. We're looking for builders who can weather the storms of groundbreaking research and come out stronger. - Mission-Driven Mindset: Everything we do is in service of creating the best spatially intelligent AI systems, and using them to empower people. - Collaborative Spirit: We're building something bigger than any one person. We need team players who can harness the power of collective intelligence. We're hiring the brightest minds from around the globe to bring diverse perspectives to our cutting-edge work. If you're ready to work on technology that will reshape how machines perceive and interact with the world - then World Labs is your launchpad. Join us, and let's make history together. Logistics: Location: This role is based in San Francisco, California; we work in-person in the office 5 days a week. Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together. Benefits: We offer generous health, dental, vision and 401K benefits, flexible PTO, paid parental leave, and relocation support as needed. Equal Employment Opportunity World Labs is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, veteran status, or any other characteristic protected under applicable law. We welcome all qualified applicants and are committed to providing reasonable accommodations throughout the hiring process upon request.

Requirements

Must-haves

While not required, experience in one or more of the following areas is a strong plus:
Large-scale model training
Data curation for pre-training or post-training
Tokenizers and VAEs for image, video, or 3D data
Long-context architectures
Design, implement, and train large-scale diffusion models for generating 3D worlds
Develop and experiment with large-scale diffusion models to add novel control signals, adapt to target aesthetic preferences, or distill for efficient inference
Collaborate closely with research and product teams to understand and translate product requirements into effective technical roadmaps.
Contribute hands-on to all stages of model development including data curation, experimentation, evaluation, and deployment.
Continuously explore and integrate cutting-edge research in diffusion and generative AI more broadly
Act as a key technical resource within the team, mentoring colleagues, and driving best practices in generative modeling and ML engineering
3+ years of experience in generative modeling or applied ML roles, ideally at a startup or other fast-paced research environment
Extensive experience with machine learning frameworks such as PyTorch or TensorFlow, especially in the context of diffusion models and other generative models
Deep expertise in at least one area of generative modeling: pre-training, post-training, diffusion distillation, fine-tuning with new conditioning signals, etc for diffusion models
Strong history of publications or open-source contributions involving large-scale diffusion models
Strong coding proficiency in Python and experience with GPU-accelerated computing.
Ability to engage effectively with researchers and cross-functional teams, clearly translating complex technical ideas into actionable tasks and outcomes.
Comfortable operating within a dynamic startup environment with high levels of ambiguity, ownership, and innovation.
Fearless Innovator: We need people who thrive on challenges and aren't afraid to tackle the impossible.
Resilient Builder: Impacting Large World Models isn't a sprint; it's a marathon with hurdles. We're looking for builders who can weather the storms of groundbreaking research and come out stronger.

Nice-to-haves

Contributions to open-source projects in the fields of computer vision, graphics, or ML.
Familiarity with large-scale training infrastructure (e.g., multi-node GPU clusters, distributed training environments).
Experience integrating machine learning models into production environments.
Led or been involved with the development or training of large-scale, state-of-the-art generative models

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningmlpython

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401k

Pto

Parental Leave