岗位大厅/Other/Research Scientist (Generative Modeling)

World Labs · 320天前 · 来源 ATS 官方

Research Scientist (Generative Modeling)

San Francisco办公方式未标注
全职Other
薪资未披露

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⏳ 岗位入库已 0 天

🛡 申请链接 2026-11-08 核验有效

📈 该公司近 30 天发布 8 个岗位——扩张招聘中,属加分信号

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必备技能

AIComputer VisionDistributed TrainingFine TuningGPUGenerative AILLMNode.jsPyTorchPython

免费注册后解锁"你的匹配分 vs 高分画像"与个人技能缺口。

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职位描述

About World Labs World Labs 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 , Justin Johnson and Ben Mildenhall , the company is pioneering world models that perceive, generate, reason, and interact with virtual and physical worlds.

The company’s flagship product, Marble , 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.

🈯 翻译这份 JD · 红灯 0 / 黄灯 1 / 绿灯 2点开 ▾
可以投——没有红灯,黄灯问题放进面试清单问清即可。 另有 1 条主动欢迎信号——加分。
🤝 reasonable accommodations → 承诺提供合理便利(面试可提要求)
fast-paced → 流程不成熟、需求常变要问的问题:「节奏快」的交付周期是多久?需求由谁定?
deep expertise → 「用过能干活」级——符合 60% 就值得投
plus → 加分项,不是门槛
词典只标"常见信号",不对公司下结论——红灯 = 面试里该当面确认的问题。想自己翻别的 JD:JD 翻译器 →
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公司 · Company

World Labs

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San Francisco来源:ATS 官方

⚑ 岗位信息收录自公开招聘页(ATS 官方),以雇主官网为准