Head of Psysical AI

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  Audit Miraxis’s data, evaluation assets, partnerships, and model opportunities.

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  Select one or two focused research bets.

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  Establish a reproducible model baseline and initial evaluation suite.

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  Define a credible path to physical validation.

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  Present a practical 12-month roadmap supported by working technical evidence.

• Train, adapt, or rigorously evaluate at least one relevant Transformer-based model or robot policy.

• Confirm or reject at least one important technical hypothesis.

• Establish a repeatable data-to-training-to-evaluation workflow.

• Test on a real robot, directly or through a credible hardware partner.

• Document representative failures and their implications.

• Demonstrate a measurable improvement attributable to Miraxis data, methods, or assurance systems.

• Close the loop between model failures, data decisions, retraining, and re-evaluation.

• Deliver a model, benchmark, evaluation system, or deployment that a customer or partner can use.

• Build a small team capable of running the work without unnecessary process layers.

Success will be judged by decision quality, reproducibility, real-system results, and customer value—not by team size, paper count, parameter count, or experiment volume.