Head of Psysical AI

The role

You will establish and lead the AI research and engineering function by deciding which Physical AI problems to pursue and defining evaluation methods. You will act as a player-coach, spending at least half of your first year on direct technical work including designing models, writing code, and analyzing failures.

What you will do

• Define a focused Physical AI research and engineering roadmap.
• Select model families to train, adapt, or evaluate.
• Personally design, adapt, train, and evaluate Transformer-based systems.
• Define sensors, modalities, annotations, and quality controls for training.
• Establish reproducible offline and real-world evaluation systems.
• Take projects from problem definition through training and hardware integration.
• Analyze failures across data, perception, models, control, and hardware.
• Design safe, staged physical testing and deployment plans.
• Recruit and lead a small team of researchers and engineers.
• Translate customer and partner needs into technical requirements.

Required qualifications

• Material architecture or training decisions in at least one substantial Transformer-based system.
• Experience with machine learning for a system that perceives or acts in the physical world.
• At least one substantial project progressed into a real or operational physical system.
• Strong Python engineering skills.
• Direct experience with PyTorch or an equivalent deep-learning framework.
• Ability to read and debug unfamiliar model and training code.
• Experience designing controlled experiments and analyzing rollout failures.
• Experience working with large multimodal datasets.
• Sound judgment around compute, memory, training stability, inference latency, and cost.
• Experience setting direction for a significant research, model-development, robotics, or cross-functional technical program.
• Direct technical ownership.

Nice to have

• Deep Transformer expertise combined with strong computer-vision experience.
• Visual representation learning
• VLMs and video or temporal modeling
• Detection, segmentation, and tracking
• Multi-view and egocentric vision
• 3D and spatial reasoning
• Pose estimation, calibration, and localization
• Sensor fusion
• Real-time vision systems
• Vision-language-action models or robot foundation models

About the company

Miraxis builds the data, evaluation, and deployment layer for Physical AI. The company is hardware- and model-agnostic and works across multimodal robot and human data, annotation, and model evaluation.