Lead Research Scientist, Interpretable Physical AI

World Mechanics; San Francisco (CA); On-site; USD 300,000 - 500,000; Full time

Benefits offered by this job

Flexible working hours

Conference travel support

Office space and in-person collab

High ownership role

Real-world impact research

Job summary

World Mechanics is seeking a Senior Research Scientist (US) to lead end-to-end research programs across white-box evaluation, interpretable model training, and simulation for physical systems. You will set direction for multimodal world models, establish milestones, and mentor researchers while collaborating with leadership and customers to translate real needs into capabilities.

The role emphasizes empirical rigor, ownership, and high initiative in an early-stage company.

Qualifications

• Track record of high-impact ML research
• Ability to generate original research directions
• Startup alignment: high agency and fast iteration
• Pragmatic, empirical mindset with focus on real-world impact
• Strong writing and communication skills

Responsibilities

• Own end-to-end research programs aligned with core agenda from problem selection to validation and documentation
• Set technical direction across world models trained on video, sensor, time-series, and multimodal data
• Set milestones, de-risk unknowns early, and make high-quality calls on next steps
• Drive research practice: experimental design, iterations, ablations, evaluation, and write-ups
• Mentor researchers and engineers; provide technical guidance and potential management
• Partner with leadership/customers to translate needs into repeatable capabilities
• Lead and supervise publications and model releases

Job description

World Mechanics is seeking a Senior Research Scientist (US) to lead end-to-end research programs across white-box evaluation, interpretable model training, and simulation for physical systems. You will set direction for multimodal world models, establish milestones, and mentor researchers while collaborating with leadership and customers to translate real needs into capabilities.

The role emphasizes empirical rigor, ownership, and high initiative in an early-stage company.