Senior Research Engineer - Multimodal World Models (Hybrid)

Enigma; Palo Alto (CA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Enigma in Palo Alto is seeking a Senior Research Engineer/Scientist to drive world models and multimodal AI research, bridging cutting-edge theory with scalable systems. You will explore novel architectures, temporal reasoning, and scalable training to push the boundaries of autonomous intelligence in real-world contexts.

The role offers collaboration across research and engineering teams, opportunities for publications, and a hands-on impact on production-ready AI systems.

Qualifications

• Strong background in Generative AI.
• Experience with robotics or autonomous systems.
• Background in adjacent research fields.

Responsibilities

• Develop novel approaches extending current transformer and diffusion-based methods for world modelling and multimodal AI.
• Research new model architectures, training paradigms, and representations for temporal reasoning, dynamics, and interaction.
• Take ideas from initial hypothesis through experimentation to robust working prototypes.
• Design, implement, and optimise large-scale distributed training and inference infrastructure.
• Collaborate closely across research and engineering disciplines to translate scientific advances into production-ready systems.
• Contribute to the wider technical community through publications, open research where appropriate, and the development of reusable tools and infrastructure.
• Help shape the technical direction and research culture of a fast-moving AI organisation.

Skills

Generative AI

Robotics or autonomous systems

Adjacent research fields

Job description

Enigma in Palo Alto is seeking a Senior Research Engineer/Scientist to drive world models and multimodal AI research, bridging cutting-edge theory with scalable systems. You will explore novel architectures, temporal reasoning, and scalable training to push the boundaries of autonomous intelligence in real-world contexts.

The role offers collaboration across research and engineering teams, opportunities for publications, and a hands-on impact on production-ready AI systems.