MOTS - World Models

Alexander Chapman; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Alexander Chapman in Palo Alto seeks highly technical researchers and engineers to advance world models, video generation, multimodal AI, robotics, and autonomous systems. You will turn research into real‑world systems by designing training, evaluation, and inference pipelines, and by taking ideas from hypothesis to production‑ready prototypes across teams.

This role emphasizes ownership, rigorous evaluation, and collaboration with research, engineering, and product to ship breakthrough

Qualifications

• Deep technical experience in world models, generative modeling, video, multimodal learning, robotics, or large‑scale ML.
• Experience with conditioning or learned control is valuable.
• Comfortable bridging research and production, with understanding of model quality, scalability, latency, and real‑world constraints.
• Able to operate in ambiguous, fast‑moving environments without established playbooks.
• Have a strong perspective on where AI and world models need to go next—not simply “bigger models and more compute.”

Responsibilities

• Develop new approaches to world models and controllable video generation, pushing beyond diffusion and transformer-based methods.
• Build conditioning and control techniques for actions, cameras, physics, style, and long-horizon consistency.
• Take research from hypothesis to experiment to production-ready prototype.
• Design large-scale training, evaluation, and inference systems that enable new model capabilities.
• Develop rigorous evaluations for controllability, reliability, and real‑world performance.
• Work closely across research, engineering, and product to turn breakthroughs into products.
• Contribute to the broader research community through publications, technical tools, and collaboration.

Skills

World models

Generative modeling

Video generation

Multimodal learning

Robotics

Large-scale ML

Research to production

Job description

We’re looking for highly technical researchers and engineers working across world models, video generation, multimodal AI, robotics, autonomous systems, and related areas.

Our Applied Research team turns frontier research into real-world systems. Whether you specialize in developing new models, scaling training, building inference systems, or taking research into production, we want people who can turn ideas into working technology.

What You’ll Do

• Develop new approaches to world models and controllable video generation, pushing beyond current diffusion and transformer-based methods.
• Build conditioning and control techniques for actions, cameras, physics, style, and long-horizon consistency.
• Take research from hypothesis to experiment to production-ready prototype.
• Design large-scale training, evaluation, and inference systems that enable new model capabilities.
• Develop rigorous evaluations for controllability, reliability, and real‑world performance.
• Work closely across research, engineering, and product to turn breakthroughs into products.
• Contribute to the broader research community through publications, technical tools, and collaboration.

Who You Are

• Deep technical experience in world models, generative modeling, video, multimodal learning, robotics, or large‑scale ML. Experience with conditioning or learned control is especially valuable.
• Strong first‑principles thinker who can define problems, develop hypotheses, and build experiments from scratch.
• Comfortable bridging research and production, with an understanding of model quality, scalability, latency, and real‑world constraints.
• Comfortable operating in ambiguous, fast‑moving environments without established playbooks.
• Have a strong perspective on where AI and world models need to go next—not simply “bigger models and more compute.”
• Thrive in small, autonomous teams with a high degree of ownership and collaboration.
• Excited about shaping how AI perceives, learns, generates, and interacts with the visual world.