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Head of Psysical AI

G2i Inc.· Direct&Permanent Hires
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EuropeFull-timePosted 1mo ago

About the role

Head of Physical AI role leading AI research and engineering for a Multimodal, physics-oriented AI systems company. Hands-on technical leader who defines research roadmap, selects model families, and builds a small team to advance transformer-based embodied tasks from problem definition through real-world validation.

Responsibilities

  • Define a focused Physical AI research and engineering roadmap with clear hypotheses, baselines, milestones, success measures, and stop criteria.
  • Select the model families Miraxis should train, adapt, or evaluate and determine when to build internally, use open models, license technology, or work through partners.
  • Personally design, adapt, train, and evaluate Transformer-based systems for embodied tasks.
  • Work across areas such as vision-language-action models, multimodal Transformers, robot foundation models, action representation, imitation learning, reinforcement learning, world models, cross-embodiment transfer, and robot-policy evaluation.
  • Define the sensors, modalities, annotations, data mixtures, coverage, and quality controls required to train and evaluate selected models.
  • Measure how data quality, diversity, and composition affect model behavior and real-world task performance.
  • Establish reproducible offline and real-world evaluation systems, baselines, held-out conditions, and release gates.
  • Protect evaluations against leakage, overfitting, and weak or misleading success criteria.
  • Take projects from problem definition through training, hardware integration, and real-world validation.
  • Analyze failures across data, perception, models, control, hardware, and the operating environment.
  • Design safe, staged physical testing and deployment plans with clear supervision and rollback mechanisms.
  • Recruit and lead a small team of complementary researchers and engineers.
  • Lead architecture, experiment, code, rollout, and failure reviews.
  • Translate customer and partner needs into testable technical requirements.
  • Communicate technical strategy, evidence, uncertainty, and limitations clearly to customers, partners, and investors.

Qualifications

  • Deep, hands-on Transformer expertise (e.g., Vision Transformers, Vision-language or vision-language-action models, Multimodal foundation models, Decision Transformers, Diffusion Transformers, Video Transformers, World models, Transformer-based perception, planning, or control systems).
  • Physical AI experience (machine learning for systems perceiving or acting in the physical world; real or operational physical system projects).
  • Hands-on technical ability (strong Python engineering, PyTorch or equivalent, debugging, controlled experiments, large multimodal datasets, compute/memory/training stability considerations).
  • Technical leadership (previous direction of significant research or robotics/technical programs; direct technical ownership).
  • Preferred: combination of deep Transformer expertise with strong computer-vision experience (e.g., visual representation learning, VLMs, detection/segmentation/tracking, 3D, pose estimation, sensor fusion, real-time vision).
  • PhD or equivalent experience valuable but not required.

Skills

Required:Transformer-based model design and trainingPython programmingPyTorch or equivalent DL frameworkExperiment design and analysisMultimodal data handlingRobotics/physical system deploymentTechnical leadership
Last updated Sep 17, 2026. Interested? Apply on the company site.

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