About Grafton Sciences
We’re building AI systems with general physical ability — the capacity to experiment, engineer, or manufacture anything. We believe achieving this is a key step towards building superintelligence. With deep technical roots and real-world progress at scale (e.g., a $42M NIH project), we’re pushing the frontier of physical AI. Joining us means inventing from first principles, owning real systems end-to-end, and helping build a capability the world has never had before.
About the Role
We’re seeking a Senior Digital Twin ML Engineer to build high-fidelity digital twins of robotic, electromechanical, and experimental systems. You’ll design model-identification pipelines, calibration routines, dynamic-model learning systems, and multi-scale representations that enable accurate predictive simulation and closed-loop interaction with RL, planning, and control stacks. This role blends physics intuition, ML modeling, and hands-on experimentation to ensure digital twins remain stable, accurate, and continuously updated as real systems evolve.
Responsibilities
• Develop model-identification pipelines, parameter fitting routines, and adaptive calibration systems for digital twins.
• Build ML-based dynamic models, multi-scale physics approximators, and hybrid simulation frameworks.
• Ensure twin fidelity, stability, and cross-version consistency as real systems change or new data arrives.
• Collaborate with simulation, RL, controls, and agent systems teams to integrate digital twins into learning and decision-making workflows.
Qualifications
• Strong experience building or calibrating digital twins, dynamic models, or data-driven physics models.
• Familiarity with system identification, time-series modeling, physical parameter estimation, and stability/fidelity considerations.
• Ability to blend physics, machine learning, and experimental data into robust predictive models.
• Comfortable working across ML, simulation tools, and physical hardware interfaces in a fast-moving research and engineering environment.
Above all, we look for candidates who can demonstrate world-class excellence.
Compensation
We offer competitive salary, meaningful equity, and benefits.
Top Skills
What We Do
Grafton Sciences is pioneering AI systems with general physical ability, the capacity to experiment, engineer, or manufacture anything. By pairing this physical substrate with advanced learning architectures, our goal is to build superintelligence. Backed by leading partners, including ARPA-H, we are redefining how the physical world is queried at scale.
