Senior Digital Twin ML Engineer jobs in United States
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Grafton Sciences · 19 hours ago

Senior Digital Twin ML Engineer

positionSan Francisco Bay Area
timeFull-time
remoteOnsite
senioritySenior Level

Grafton Sciences is building AI systems with general physical ability, aiming to push the frontier of physical AI. The role involves developing high-fidelity, physics-based digital twins of complex machines, requiring expertise in multi-physics modeling and integration of various evidence sources.

Machine LearningRobotics
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H1B Sponsor Likelynote

Responsibilities

Build and maintain multi-domain digital twins capturing key coupled physics
Develop model identification + calibration pipelines: parameter estimation, uncertainty characterization, experiment design, and automated regression testing for twin fidelity
Combine evidence from first-principles simulators, empirical models, reduced-order models, and surrogates (data-driven or otherwise); choose the right tool per subsystem and operating regime
Create validation workflows: residual analysis, sensitivity studies, robustness checks, drift detection, and version-to-version consistency
Partner with controls/simulation/robotics teams to ensure the twin is usable for prediction, planning, control, and what-if analysis (and RL if/when relevant)

Qualification

Physics-based digital twinsMulti-physics modelingParameter estimationNumerical methodsProgramming (Python/C++/MATLAB)Machine learningGrounding in dynamicsDebugging skills

Required

Proven experience building/calibrating physics-based digital twins or high-fidelity dynamic models of complex hardware
Strong grounding in areas like: rigid/flexible-body dynamics, structural dynamics, vibrations, thermal modeling, controls, system ID, parameter estimation, numerical methods
Track record dealing with cross-coupled effects (e.g., thermal drift causing alignment error, vibration impacting sensing/actuation, stiffness changes with temperature, etc.)
Comfortable moving between simulation + real-world data: instrumentation, logging, synchronization, sanity checks, and debugging
Strong programming ability (typ. Python/C++/MATLAB) and fluency with simulation toolchains (FEM/MBD/CFD/controls stacks—specifics flexible)

Preferred

Background in machine learning

Benefits

Meaningful equity
Benefits

Company

Grafton Sciences

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Building systems of general physical ability to enable superintelligence
dateFounded in 2024
location
Redwood City, California, USA
people-size11-50 employees
web-link
https://www.graftonsciences.com/

H1B Sponsorship

Grafton Sciences has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (2)

Funding

Current Stage
Early Stage
Company data provided by crunchbase